7 - CERBERUS_Preparatory_Semantic_Grooving_Formal_Specification_v0.1.docx

CERBERUS PREPARATORY SEMANTIC GROOVING Background Semantic Accretion, Retroactive Model Enrichment, and Query-Ready Knowledge Routing CORE SYSTEM STATEMENT Interpret when compute is cheap so meaning is ready when attention is expensive. Preparatory Semantic Grooving converts low-demand compute into persistent semantic structure that later queries can route through before reopening source material. Formal Specification v0.1 15 August 2026 | CERBERUS / GROOVE / Routing SK / 000-00 / Bits Before Tokens Status: Draft reference architecture for preparatory scheduling, backfill, semantic readiness, and query-time routing experiments. Document Control Field Specification Document CERBERUS Preparatory Semantic Grooving - Formal Specification Version 0.1 Date 15 August 2026 System CERBERUS / GROOVE / Routing Semantic Kernels / 000-00 / Bits Before Tokens Specification role Defines the operational lifecycle for background and low-demand semantic preparation of new and historical Entries. Primary design boundary PSG adds versioned semantic projections, routing metadata, Bundle membership, and preparation state. It does not rewrite source truth or silently promote interpretive output into canonical identity. Implementation status Draft for prototype queueing, backfill, scheduling, interface, and semantic-yield testing. Normative vocabulary MUST, MUST NOT, SHALL, SHALL NOT, SHOULD, SHOULD NOT, MAY Abstract Preparatory Semantic Grooving (PSG) defines how a persistent knowledge system can use low-demand compute periods to make existing knowledge more semantically ready before a future question arrives. PSG treats semantic preparation as explicit queued work: new Entries can receive broad and fine GROOVE passes at ingestion, new Routing SKs and Models can be applied retroactively to historical material, stale projections can be re-GROOVEd, and incomplete Bundle metadata can be repaired without blocking interactive use. The architecture is deliberately accretive. A historical Entry is not considered semantically finished when first ingested. When a new semantic instrument becomes available, existing GROOVE projections can identify the portion of the corpus most likely to benefit. PSG then applies the new instrument only where warranted, preserves the resulting Projection beside earlier interpretations, updates 00 and 000 reach, and records the semantic reach added by the job. The source Entry remains unchanged and authoritative for its substantive content. The query-time payoff is direct. Bits Before Tokens can route future requests through semantic work that has already been performed: Routing SK coordinates, branch-conditioned descriptions, Bundle memberships, Models, Operators, Rules, and source locators. Expensive source reopening occurs later and over a smaller candidate set. PSG therefore turns spare compute into persistent semantic reach and amortizes interpretation across many later searches, comparisons, constructions, and simulations. THESIS The long-term semantic value of a corpus is not fixed at ingestion. New semantic instruments can reveal new structure in old material, and low-demand compute can preserve that structure before future queries need it. Companion Architecture Basis Companion artifact Role in this specification GROOVE - Grounded Relations Over Observable Versioned Entries v1.0 Provides Observable Versioned Entries, 000/00 routing, source authority, relation review, and persistent orientation around source material. CERBERUS Routing Semantic Kernels v0.1 Provides bounded routing contracts, route state, nested semantic depth, and the rule that the Router owns the route while the destination owns its meaning. GROOVE Routing Semantic Kernels Add-On v0.1 Provides multifactor Entry Routing States, semantic branch factorization, recursive resolution, and non-merging structural semantic reuse. CERBERUS Bits Before Tokens v0.1 Provides the query-time consumer of prepared semantic structure: hierarchical routing, Semantic Fade, 000/00 retrieval, and selective source reopening. Contents Section Title 0 Executive Summary 1 Purpose and Scope 2 Problem Statement 3 Core Thesis and Architectural Position 4 Formal Definition 5 Operational Modes 6 Semantic Amortization Part I Preparatory Semantic Work 7 Forward PSG 8 Retroactive PSG 9 Re-GROOVE 10 Maintenance PSG 11 PSG Lifecycle Part II PSG Jobs and Pass Architecture 12 PSG Job Object 13 Target Corpus and Target Scope 14 Eligibility Surfaces 15 Pass Stacks and Sweep Profiles 16 Conditional and Branching Passes 17 Persistence Policy 18 Completion Criteria Part III Retroactive Enrichment and Backfill 19 New Semantic Instruments 20 Backfill Frontier 21 GROOVE Routes GROOVE 22 Selective Backfill 23 Exploratory Sampling 24 Semantic Reach Expansion 25 Semantic Reach Delta Part IV Semantic Readiness, Versioning, and Maintenance 26 Semantic Readiness 27 Readiness Profiles 28 Projection Lineage 29 Staleness and Impact Analysis 30 Source Authority and Applicability Preservation 31 Noncanonical Interpretation Boundary Part V Compute Scheduling and Queue Governance 32 Compute Windows 33 Priority Classes 34 Interactive Priority 35 Resource Budgets 36 Queue, Pause, Resume, and Recovery Part VI Query-Ready Knowledge and Bits Before Tokens 37 Query-Ready Knowledge 38 000 and 00 Enrichment 39 Selective Source Reopening 40 Preparatory Work and Query-Time Savings 41 Metrics and Evaluation Part VII Interface Architecture 42 PSG Control Room 43 Job Builder 44 Target Scope Builder 45 Pass Stack Editor 46 Backfill Preview 47 Compute Policy and Queue 48 Readiness and Reach Interfaces 49 Next Best Preparatory Work Part VIII Worked Example 50 New Model Registration 51 Historical Eligibility 52 Backfill Execution 53 Expanded Reach 54 Later Query Retrieval Part IX Formal Principles and Conformance 55 Normative Principles 56 Failure Modes 57 Conformance Requirements 58 Implementation Roadmap 59 Conclusion Glossary Reference Terms 0. Executive Summary Preparatory Semantic Grooving moves a large portion of semantic interpretation out of the critical path of a future query. Rather than waiting until a person asks a question to discover what a note, paper, specification, diagram, or simulation result is about, the system can perform bounded GROOVE passes during low-demand periods and preserve the results as versioned semantic projections. The system operates in four modes. Forward PSG prepares newly arrived Entries. Retroactive PSG applies newly available Routing SKs, Models, or Sweep Profiles to older material. Re-GROOVE re-evaluates projections affected by meaningful source or instrument changes. Maintenance PSG repairs semantic readiness gaps such as missing branch descriptions, stale relationships, incomplete Bundle placement, or unfinished Model correspondence. The key efficiency is recursive. Existing GROOVE structure does not merely help future queries; it also helps decide where future GROOVE work is worth spending. A new Biology-specific instrument does not need to scan an entire mixed corpus if earlier broad passes already identify Biology, Materials, or adjacent semantic regions. Existing projections create an eligibility surface, the unprocessed eligible set becomes the Backfill Frontier, and PSG consumes that frontier according to priority and resource policy. The output of preparatory work is not a precomputed answer. It is query-ready semantic infrastructure: compact coordinates, branch-conditioned descriptions, explicit 00 membership, relation candidates, provenance, Model correspondence, and source locators. Future Bits Before Tokens routing can exploit this structure before loading source tokens, reducing repeated semantic reconstruction while preserving the principle that GROOVE points and the Entry proves. Preparatory Semantic Grooving Lifecycle | Low-demand semantic preparation feeds future routing while new instruments reopen old semantic territory. FORWARD New Entry -> current Sweep Profiles -> saved GROOVE Projection -> query-ready metadata RETROACTIVE New Routing SK / Model -> existing GROOVE eligibility -> historical Backfill Frontier -> new Projection MAINTAIN Changed source or instrument -> impact analysis -> Re-GROOVE -> lineage preserved EXPLOIT Future query -> 000 / 00 -> prepared semantic structure -> selective source reopen -> reasoning Prepare -> Accrete -> Route -> Reopen only what survives Figure 1. Preparatory Semantic Grooving Lifecycle. Low-demand semantic preparation feeds future routing while new instruments reopen old semantic territory. ENGINEERING SUMMARY PSG builds semantic structure before the question arrives. Bits Before Tokens spends that structure when the question arrives. 1. Purpose and Scope This specification defines PSG as an operational method for preparing knowledge artifacts for later semantic routing. It covers job definition, target selection, eligibility filtering, configurable GROOVE passes, low-demand compute scheduling, retroactive enrichment, projection lineage, semantic readiness, backfill, reach measurement, and interfaces for controlling those operations. 1.1 Goals Make new Entries semantically routable before future queries require them. Allow new Routing SKs, Models, and Sweep Profiles to enrich historical material without rewriting source content. Use existing GROOVE projections to bound later backfill work instead of repeatedly scanning the whole corpus. Keep preparatory work explicit, inspectable, pausable, versioned, and resource-aware. Measure semantic preparation by readiness and reach added, not only by documents processed. Provide query-time systems with compact semantic handles that reduce unnecessary source-token reading. 1.2 Non-goals PSG does not create canonical truth merely because a background model produced an interpretation. PSG does not require every Entry to receive every available semantic instrument. PSG does not replace original source inspection for consequential factual claims. PSG does not define one universal pass sequence or one global readiness score. PSG does not silently mutate Routing SKs, Models, SOLAR Aliases, or BIGFOOT identities. PSG does not take precedence over latency-sensitive interactive work unless explicitly configured. 2. Problem Statement A corpus can contain enormous latent value while remaining expensive to use. If every query must reopen old documents, reconstruct their domains, rediscover their relation to current Models, and infer which portions matter, the same semantic labor is paid repeatedly. The cost becomes especially visible in personal archives and evolving technical systems where new semantic structures are invented after much of the source material already exists. DESIGN PROBLEM How can a persistent knowledge system use available compute to prepare semantic structure ahead of demand, then retroactively apply new ways of seeing without confusing interpretation with source truth? 3. Core Thesis and Architectural Position PSG treats semantic interpretation as reusable infrastructure. A GROOVE pass can be performed once, persisted with its source identity, instrument version, branch context, and review state, then reused by later queries and later passes. When a new semantic instrument appears, the system can selectively revisit the historical corpus and add a new projection beside earlier ones. The corpus becomes semantically richer over time without changing the source itself. LOW-DEMAND COMPUTE | v PREPARATORY GROOVE JOB | v VERSIONED PROJECTIONS -> 00 / 000 REACH -> FUTURE ROUTING ^ | NEW ROUTING SK / MODEL / SWEEP PROFILE 4. Formal Definition FORMAL DEFINITION Preparatory Semantic Grooving is the scheduled, opportunistic, or administrator-directed application of registered GROOVE Sweep Profiles, Routing Semantic Kernels, Models, and related semantic instruments to new or previously registered Observable Versioned Entries for the purpose of increasing persistent semantic readiness, routing coverage, and future retrieval efficiency. PSG produces semantic projections and preparation state. It MAY generate candidate relations, Bundle memberships, branch-conditioned descriptions, semantic coordinates, comparison outputs, and reach reports. It SHALL preserve provenance to the source Entry and the semantic instrument used. 5. Operational Modes Table 1. PSG operational modes Mode Trigger Primary output Forward PSG New Entry or new revision arrives Initial and progressive semantic projections using currently applicable instruments. Retroactive PSG New semantic instrument or new resolution becomes available New projections over eligible historical Entries. Re-GROOVE Source, instrument, scope, or relation changed materially Re-evaluated projections with lineage to the prior version. Maintenance PSG Readiness gap, stale metadata, or unfinished semantic layer Repaired descriptions, relations, Bundle placement, or coverage state. 6. Semantic Amortization Semantic Amortization is the reuse of interpretation performed once across many later operations. The same prepared projection can support search, retrieval, Model comparison, UI orientation, cross-GROOVE synthesis, teaching, simulation setup, or a future backfill pass. PSG therefore shifts cost from repeated query-time rediscovery toward persistent semantic preparation. WITHOUT PSG: each query reopens and reclassifies source material. WITH PSG: prepare once; many later queries route through persistent semantic state. PART I - PREPARATORY SEMANTIC WORK PSG turns semantic preparation into explicit, inspectable lifecycle work rather than vague background inference. 7. Forward PSG Forward PSG processes new or materially revised Entries using the semantic instruments currently available and applicable. A deployment MAY begin with broad Routing SKs only, then add finer passes later. Initial processing should favor high-value preparation over exhaustive interpretation. NEW ENTRY -> BROAD ROUTING -> MULTIFACTOR STATE -> FACTOR BRANCHES -> 00 MEMBERSHIP -> OPTIONAL FINER PASSES 8. Retroactive PSG Retroactive PSG applies a newly introduced semantic instrument to historical Entries. The source does not need to move, be duplicated, or be re-authored. The new output is another versioned projection that increases the semantic routes through which the Entry can later be discovered. 9. Re-GROOVE Re-GROOVE is used when a source or semantic instrument changes materially enough that existing interpretation may be stale. The previous projection SHOULD remain traceable. Re-GROOVE is not silent replacement; it is a new evaluation with lineage. 10. Maintenance PSG Maintenance PSG targets semantic incompleteness rather than new content. Typical jobs include generating missing branch-conditioned descriptions, reviewing stale GROOVE relations, filling 00 manifests, validating source locators, resolving incomplete Bundle membership, or repairing coverage after an interrupted job. 11. PSG Lifecycle Discover or define preparatory work. Bind a target corpus and eligibility surface. Select or author the Pass Stack. Preview cost, coverage, and Backfill Frontier. Queue the PSG Job under an explicit compute policy. Execute passes while preserving source and projection lineage. Persist declared outputs and update readiness state. Measure Semantic Reach Delta and newly reachable 000/00 paths. Expose prepared structure to future routing and later PSG jobs. PART II - PSG JOBS AND PASS ARCHITECTURE A PSG Job is the explicit unit of preparatory semantic work. 12. PSG Job Object A PSG Job is a versioned instruction package defining what should be processed, which semantic instruments should be applied, how the passes are sequenced or branched, when compute may be consumed, what outputs should persist, and what counts as completion. Table 2. Reference PSG Job schema Field Role Example Job ID Stable work identity PSG-JOB-00418 Mode Forward / Retroactive / Re-GROOVE / Maintenance Retroactive Target Scope Corpus, Bundle, route, date, source class, or explicit Entry set Personal Notes + Materials/Biology routes Eligibility Conditions that must be satisfied before processing Existing relevance >= 0.45 OR Biology route active Pass Stack Ordered, conditional, or iterative pass definitions Route -> factor -> describe -> relate Compute Policy When and how resources may be used Low-demand only; pause above 65% interactive load Persistence Which outputs survive the job Projection, lineage, branch descriptions, Bundle membership Completion Exit condition Backfill Frontier = 0 or budget exhausted Status Lifecycle state QUEUED / RUNNING / PAUSED / COMPLETE PSG Control Room | The operator sees system load, queue state, readiness, and current semantic work before starting or changing jobs. SYSTEM LOAD Interactive31% PSG AllowedACTIVE Queue14 jobs / 3 running / 8 waiting / 3 paused PolicyLow-demand mode CURRENT WORK JobMORPHODYNAMIC_REPAIR Backfill Progress6,812 / 8,744 Entries PassBranch Description Readiness impactModel coverage +14% [ NEW PSG JOB ] [ BACKFILL FRONTIERS ] [ READINESS ] [ QUEUE ] Figure 2. PSG Control Room. The operator sees system load, queue state, readiness, and current semantic work before starting or changing jobs. 13. Target Corpus and Target Scope Target Scope defines the population a PSG Job may touch. It can be physical, semantic, temporal, structural, or any governed combination. The operator should be able to select explicit documents when needed, but the system becomes more powerful when scope can be expressed through existing semantic structure. Physical: folder, repository, database, source class, owner, project, or explicit Entry list. Semantic: 000 domain, 00 Bundle, Routing SK coordinate, multifactor intersection, Model neighborhood, or current SK. Temporal: created, revised, or last-GROOVEd date range. Coverage: missing a declared projection, below a readiness dimension, or stale under a newer instrument version. Governance: lifecycle status, permission scope, source authority class, or applicability boundary. New PSG Job Builder | A PSG Job begins with a named purpose and explicit mode before the operator selects scope and passes. JOB DEFINITION NameMorphodynamic Repair Historical Backfill ModeRETROACTIVE PurposeApply the new repair instrument to relevant historical material PriorityCurrent Project NEXT STEPS 1 Target Scope 2 Eligibility 3 Pass Stack 4 Compute Policy 5 Backfill Preview [ SAVE DRAFT ] [ NEXT: TARGET SCOPE ] Figure 3. New PSG Job Builder. A PSG Job begins with a named purpose and explicit mode before the operator selects scope and passes. Target Scope Builder | Source selection and semantic selection can be combined so PSG jobs target exactly the Entries that matter. SOURCE CORPUS [x] Personal Notes [x] Formal Specifications [x] Research Papers [ ] Images [ ] Simulation Logs DateAny SEMANTIC SCOPE [x] SCIENCE-16 : Materials [x] SCIENCE-16 : Biology [x] ENGINEERING-16 : Structural EligibilityExisting relevance >= 0.45 Adjacent sample5% of near-boundary Entries Estimated eligible Entries: 11,204 [ PREVIEW ENTRIES ] [ NEXT: PASSES ] Figure 4. Target Scope Builder. Source selection and semantic selection can be combined so PSG jobs target exactly the Entries that matter. 14. Eligibility Surfaces An Eligibility Surface is the bounded set of Entries that satisfy the target and semantic conditions of a PSG Job. Existing GROOVE projections SHOULD be used where possible so the system can avoid re-reading obviously irrelevant material before deciding whether to run a deeper instrument. PREPARATORY ROUTING PRINCIPLE Existing semantic structure should route future semantic enrichment whenever sufficient routing information already exists. Semantic Scope Tree | The operator can target existing 000/00 semantic neighborhoods instead of constructing only folder-based jobs. GLOBAL::000 Science [selected] Biology [selected] Regeneration [selected] Genetics [not selected] Materials [selected] Responsive [selected] Optical [not selected] ENGINEERING::000 Structural [selected] Marine [adjacent sample] COVERAGE Responsive Materials4,811 Entries / new Model coverage 0% Regeneration2,304 Entries / new Model coverage 18% Scope can combine branches without merging their source identities. Figure 5. Semantic Scope Tree. The operator can target existing 000/00 semantic neighborhoods instead of constructing only folder-based jobs. 15. Pass Stacks and Sweep Profiles PSG SHALL NOT define one universal pass order. A Pass Stack packages the ordered, conditional, branching, or iterative semantic operations appropriate to the job. Each pass declares its input, instrument, resolution, output, grounding requirement, continuation policy, persistence behavior, and failure route. Pass Stack Editor | The operator explicitly chooses the next passes, their order, and which outputs persist. PASS 01 - ROUTING InstrumentMORPHODYNAMIC_REPAIR-128 v1 MultifactorPreserve compatible routes OutputCombined BitWord + active routes PASS 02 - FACTORIZATION PolicySplit active routes PreserveOriginal multifactor state = YES PASS 03 - BRANCH DESCRIPTION GroundingRequired OutputBranch-conditioned GROOVE descriptions PASS 04 - RELATIONAL SWEEP ScopeResulting Bundles ReviewPROPOSED unless validated PASS 05 - MODEL COMPARISON CompareModels + FASK PromotionNone automatic [ + ADD PASS ] [ + CONDITIONAL BRANCH ] [ DRAG TO REORDER ] Figure 6. Pass Stack Editor. The operator explicitly chooses the next passes, their order, and which outputs persist. Individual Pass Configuration | A pass exposes its instrument, multifactor policy, outputs, continuation threshold, and failure behavior. ROUTING PASS InputPrevious Pass Output / Job Corpus InstrumentMORPHODYNAMIC_REPAIR-128 v1 Entry resolutionWhole Entry + Branch Context MultifactorPreserve all compatible routes OUTPUT + CONTROL [x] Combined BitWord [x] Active routes [x] Route evidence [x] Projection lineage Continue ifPreparatory relevance >= 0.40 BorderlineReview Queue FailureRemain Unresolved A deeper pass can stop without discarding the broader GROOVE already established. Figure 7. Individual Pass Configuration. A pass exposes its instrument, multifactor policy, outputs, continuation threshold, and failure behavior. 16. Conditional and Branching Passes A PSG Job may branch when previous output makes a more specialized semantic instrument appropriate. Conditional passes let broad preparation stay cheap while still permitting deep enrichment where the Entry earns it. Conditional Pass Builder | Passes can activate only when prior semantic state satisfies explicit conditions. IF Previous route includes SCIENCE-16 : Biology AND MATERIALS-64 : Responsive AND preparatory relevance >= 0.55 THEN ApplyBIOLOGY-256 PurposeLook for regenerative mechanisms NextCompare against Materials Models ElseStop this branch [ SAVE CONDITION ] [ ADD ELSE BRANCH ] Figure 8. Conditional Pass Builder. Passes can activate only when prior semantic state satisfies explicit conditions. 17. Persistence Policy Every PSG Job SHOULD declare which outputs persist and which are temporary. Persistent outputs may include Routing SK state, factored branches, branch descriptions, Bundle memberships, GROOVE relations, Model correspondence, projection lineage, semantic landing orientation, and completion metadata. Temporary intermediate LLM reasoning is not required to become part of the semantic record. 18. Completion Criteria Completion may mean the Backfill Frontier reached zero, the resource budget was exhausted, a declared readiness target was reached, a review queue was created, or a configured semantic depth was satisfied. Completion SHOULD be explicit enough that the same job can be resumed or compared later. PART III - RETROACTIVE ENRICHMENT AND BACKFILL New semantic instruments can increase the future reach of old knowledge without rewriting old knowledge. 19. New Semantic Instruments A newly introduced Routing SK, Model, Sweep Profile, or finer resolution layer can create new preparation work. Registration of the instrument SHOULD be separable from the decision to backfill it. PSG provides the control surface for deciding which historical corpus is eligible, when the work should run, and what should persist. 20. Backfill Frontier DEFINITION The Backfill Frontier is the set of Entries that are eligible for a declared semantic instrument but do not yet possess the current required GROOVE Projection. BIOLOGY-256 v1 Eligible corpus 18,441 Already current 6,119 ---------------------------- Backfill Frontier 12,322 21. GROOVE Routes GROOVE The same semantic projections that accelerate later search can accelerate later semantic preparation. A new specialist instrument should normally begin from the strongest existing coarse handles instead of blindly reopening the entire corpus. This turns semantic work persistence into recursive operational leverage. CORE PRINCIPLE GROOVE routes GROOVE. Earlier semantic work should be used to decide where later semantic work is worth spending. 22. Selective Backfill Selective Backfill applies a new instrument to the strongest eligible surface first. The target can be widened later if semantic yield or exploratory results justify it. This permits rapid high-value coverage for current projects while keeping archive-wide work lower priority. 23. Exploratory Sampling Strictly following old routes can inherit old blind spots. PSG SHOULD permit bounded exploratory samples from near-boundary or currently unclassified material. Exploratory sampling does not imply that the new Model belongs everywhere; it is a controlled mechanism for detecting missed semantic neighborhoods and calibrating eligibility rules. Backfill Preview | Before queueing a large retroactive job, the operator can inspect frontier size, predicted work, and expected yield. CORPUS ESTIMATE Total corpus184,220 Eligible by existing GROOVE11,204 Already current2,460 BACKFILL FRONTIER8,744 WORK ESTIMATE Estimated passes31,882 Source reopenings1,104 High-yield candidates2,104 Medium-yield4,310 Exploratory2,330 [ VIEW SAMPLE ] [ SAVE JOB ] [ QUEUE ] Figure 9. Backfill Preview. Before queueing a large retroactive job, the operator can inspect frontier size, predicted work, and expected yield. 24. Semantic Reach Expansion DEFINITION Semantic Reach Expansion is the increase in the set of future queries, semantic neighborhoods, Models, Bundles, and routing paths through which an existing Entry can be discovered after new GROOVE Projections are added. An old note may have been reachable only through broad Materials and Biology routes at first. After a new repair Model is applied, the same note may also become reachable through Morphodynamic Repair, Regeneration, a new 00 Bundle, and cross-GROOVE intersections. The source is identical; the semantic paths into it have increased. 25. Semantic Reach Delta Semantic Reach Delta describes what a PSG Job added to discoverability. It should report meaningful new paths rather than only throughput. Useful measures include newly reachable Entries, new Bundle memberships, new Model correspondences, new cross-GROOVE surfaces, formerly isolated Entries connected to active semantic territory, and new candidate work revealed by the pass. PART IV - SEMANTIC READINESS, VERSIONING, AND MAINTENANCE Prepared knowledge remains inspectable, versioned, and revisitable. 26. Semantic Readiness Semantic Readiness describes how much useful preparatory structure exists around an Entry, Bundle, or corpus for a declared class of future operations. It is multidimensional. A source can have broad routing complete while fine routing, relations, Model correspondence, or branch descriptions remain unfinished. 27. Readiness Profiles Table 3. Example semantic readiness profile Readiness dimension Example state Meaning Broad routing COMPLETE Entry has current top-level Routing SK projections. Branch factorization COMPLETE Multifactor states have persisted independently traversable branches. Fine routing PARTIAL Some eligible branches have not received specialist passes. Descriptions COMPLETE Branch-conditioned orientation is available. Relations PARTIAL Candidate or reviewed GROOVE relations remain incomplete. Model correspondence PENDING A newly introduced Model has not been backfilled. Interfaces MAY display a summary percentage for convenience, but the underlying dimensions SHOULD remain inspectable. A single readiness number is not a substitute for knowing which semantic layer is missing. 28. Projection Lineage Preparatory outputs SHOULD preserve the Entry identity, source version, instrument identity and version, Sweep Profile, pass configuration, timestamp, review state, and parent Projection where applicable. A later Projection may supersede another for one use without erasing historical interpretive lineage. 29. Staleness and Impact Analysis When a source revision, Routing SK version, Model contract, or governing rule changes, PSG can identify projections that may have become stale. Impact analysis creates targeted Re-GROOVE work rather than treating the entire archive as invalid. 30. Source Authority and Applicability Preservation PSG does not recalculate source authority merely because it adds a new semantic route. A Company Standard can remain authoritative in its governed scope; a Game Law can remain authoritative inside its game and inapplicable elsewhere. Preparatory classification expands retrieval reach while preserving the source and governance layers that determine authority and applicability. 31. Noncanonical Interpretation Boundary BOUNDARY A PSG Projection is an interpretation of an Entry under a declared semantic instrument. It is not evidence that the Entry defined, influenced, or canonically belongs to the semantic structure used to interpret it unless a separate governed relation establishes that fact. PART V - COMPUTE SCHEDULING AND QUEUE GOVERNANCE Preparatory work is opportunistic: it should use spare capacity without stealing from interactive cognition. 32. Compute Windows A PSG deployment SHOULD define when preparatory work may consume resources. Conditions can include interactive load, elapsed idle time, overnight windows, power availability, cost windows, local device state, worker availability, or explicit manual permission. The architecture does not require a cloud scheduler; the same policy can control a local runtime. PSG Compute Policy | Low-demand work is governed by explicit start, pause, and resource rules. RUN WHEN [x] Interactive load < 40% [x] System idle > 10 minutes [x] Overnight 23:00 - 07:00 Max concurrent jobs3 Max source readers2 PAUSE WHEN [x] User begins latency-sensitive task [x] Interactive load > 65% [x] Manual pause ResumeWhen conditions recover Current modeLOW-DEMAND Interactive work remains first-class; PSG yields unless explicitly configured otherwise. Figure 10. PSG Compute Policy. Low-demand work is governed by explicit start, pause, and resource rules. 33. Priority Classes Table 4. Illustrative PSG priority classes Priority Typical work Rationale P0 New Entry basic GROOVE Keeps newly arriving material routable. P1 Current-project backfill Directly improves active work. P2 New Model / Routing SK backfill Expands historical semantic reach. P3 Stale projection repair Maintains correctness and traceability. P4 Deep relational sweeps Useful but not latency critical. P5 Archive-wide exploration Lowest urgency; ideal for long idle windows. 34. Interactive Priority INTERACTIVE PRIORITY PRINCIPLE Preparatory semantic work SHOULD yield to user-facing or latency-sensitive operations unless the operator explicitly configures a different policy. 35. Resource Budgets Jobs MAY carry limits for source reopenings, LLM calls, token use, worker count, elapsed time, cost, memory, or semantic depth. Resource budgets let a job make useful partial progress while remaining safe to pause and resume. 36. Queue, Pause, Resume, and Recovery PSG Jobs SHOULD be resumable from durable checkpoints. A pause must not require redoing successful passes. Failed or blocked Entries should move to an explicit exception state so the remainder of the frontier can continue. PSG Queue Manager | The queue exposes priority, mode, progress, and controls without hiding work inside background model state. P0 New Entries - Today | Forward | RUNNING P1 Morphodynamic Repair | Retroactive | RUNNING Prosopohermeneia Backfill | Retroactive | 41% P2 Materials-64 v2 | Re-GROOVE | WAITING P3 Bio-Materials Relations | Maintenance | WAITING P5 2019 Note Archive | Exploratory | PAUSED [ PAUSE ] [ RESUME ] [ REORDER ] [ INSPECT ] [ CANCEL ] Figure 11. PSG Queue Manager. The queue exposes priority, mode, progress, and controls without hiding work inside background model state. Live Job Monitor | Running jobs expose concrete semantic outputs and current worker state. MORPHODYNAMIC REPAIR BACKFILL Progress78% Processed6,812 Remaining1,932 Current EntryNOTE-004119 Current PassBranch Description OUTPUT SO FAR Combined BitWords6,812 Factored branches9,441 New Bundle links3,182 Descriptions2,771 Relations618 Worker state: LOW-DEMAND MODE [ VIEW CURRENT ENTRY ] [ PAUSE ] Figure 12. Live Job Monitor. Running jobs expose concrete semantic outputs and current worker state. PART VI - QUERY-READY KNOWLEDGE AND BITS BEFORE TOKENS Preparatory work earns its value when later queries can route through it before spending source tokens. 37. Query-Ready Knowledge Query-ready knowledge is not a prewritten answer. It is a source-grounded semantic surface containing enough persistent structure that a future router can cheaply determine where to look next. Typical components include Entry identity, current GROOVE coordinates, branch descriptions, Bundle membership, relation state, Model correspondence, source locator, version, authority metadata, and preparation lineage. 38. 000 and 00 Enrichment As PSG adds projections, the 000 and 00 network becomes richer. An Entry can gain a new branch membership without moving physically. A newly populated 00 Bundle can then become reachable through a domain 000. Preparatory work therefore expands semantic topology as well as per-document metadata. 39. Selective Source Reopening Prepared metadata remains an orientation layer. When a future answer depends on specific evidence, the retrieval system should reopen the selected Entry and inspect the grounded source context. PSG is valuable precisely because it reduces how many sources must reach this expensive stage. 40. Preparatory Work and Query-Time Savings The query-time system can compare a request path against semantic work performed earlier. Entries with incompatible routes can drop before source reading; branch descriptions can provide warm reads; only the strongest candidates require full-fidelity reopening. The benefit compounds as more of the corpus becomes prepared and as new specialist Models expand old reach. 41. Metrics and Evaluation Table 5. PSG evaluation metrics Metric Question answered Backfill Frontier How much eligible work remains for this instrument? Readiness dimensions Which preparation layers are complete, partial, stale, or missing? Semantic Reach Delta What new discovery paths did the job add? Source reopen rate How often did a pass need full-fidelity source access? Reuse count How many later operations consumed a saved Projection? Query reduction How much source material was excluded before token-heavy reading? Staleness rate How often are projections invalidated by source or instrument changes? Yield per compute unit How much useful semantic coverage was added relative to job cost? PART VII - INTERFACE ARCHITECTURE The PSG interface is a semantic job scheduler, compiler surface, and knowledge-maintenance console. 42. PSG Control Room The Control Room is the system-level overview already shown in Figure 2. It should surface load, queue state, readiness, active jobs, and semantic coverage gaps without requiring the operator to inspect low-level worker logs. 43. Job Builder The Job Builder should progressively ask for purpose, mode, target scope, passes, compute policy, and persistence. The operator should be able to save a draft before all details are known. A job becomes runnable only when its required fields and permissions validate. 44. Target Scope Builder The Target Scope Builder must support explicit documents and semantic targeting. Useful selectors include current SK, 00 Bundle, Routing SK coordinate, multifactor intersection, source type, date, project, missing Projection, readiness gap, and instrument version. Scope preview should show representative Entries and estimated frontier size. 45. Pass Stack Editor The Pass Stack Editor should allow insertion, reordering, branching, looping, stopping, and conditional execution. Every pass should expose its input, instrument, output, grounding requirement, persistence policy, and continuation behavior. The visual design should make it obvious that PSG passes are configuration, not a universal fixed pipeline. 46. Backfill Preview Backfill Preview acts as the cost-and-yield checkpoint before queueing. It should show total corpus size, eligibility reduction from existing GROOVE, current coverage, Backfill Frontier, predicted passes, estimated source reopenings, and a sample of high-yield and boundary cases. 47. Compute Policy and Queue Compute Policy lets the operator define conditions under which PSG is allowed to run. Queue controls should be ordinary: inspect, reorder, pause, resume, cancel, retry, and lower resource usage. A semantic background system is safer when it behaves like visible work rather than invisible autonomous cognition. 48. Readiness and Reach Interfaces Readiness and reach interfaces translate background semantic work into visible maintenance choices. They should show which semantic layers are missing, which historical Entries gained new routes, and where the next useful backfill frontier exists. Semantic Readiness Explorer | Readiness is shown by layer so the operator can choose useful preparatory work rather than chasing one opaque score. CORPUS COVERAGE Personal Notes Route 100% | Fine 74% | Desc 91% | Rel 42% | Models 63% Research Papers Route 98% | Fine 89% | Desc 82% | Rel 76% | Models 81% Specifications Route 100% | Fine 96% | Desc 99% | Rel 93% | Models 88% Images Route 71% | Fine 41% | Desc 33% | Rel 12% | Models 18% DRILLDOWN Personal Notes -> Fine Routing 74% Missing: 1,441 Entries across 3 active Backfill Frontiers Highest current-project gap: Prosopohermeneia-128 [ OPEN FRONTIER ] [ CREATE MAINTENANCE JOB ] Figure 13. Semantic Readiness Explorer. Readiness is shown by layer so the operator can choose useful preparatory work rather than chasing one opaque score. Projection Timeline | One old Entry can accumulate new semantic projections over time while its source content remains unchanged. NOTE-001844 Created2022 Source changed?NO 2026-08-15 SCIENCE-16 v1 -> Materials + Biology 2026-08-16 MATERIALS-64 v1 -> Responsive Materials 2026-10-03 BIOLOGY-256 v1 -> Regenerative Structures 2027-02-11 MORPHODYNAMIC_REPAIR-128 v1 -> Repair Through Morphological Growth The note did not change. The semantic routes through which it can be found did. Figure 14. Projection Timeline. One old Entry can accumulate new semantic projections over time while its source content remains unchanged. Semantic Reach Delta Report | The completion report emphasizes new semantic access, not only processing throughput. BEFORE Reachable Entries2,812 Active Bundle paths7 Connected Models3 Cross-GROOVE surfaces2 AFTER Reachable Entries4,113 (+1,301) Active Bundle paths14 (+7) Connected Models8 (+5) Cross-GROOVE surfaces5 (+3) Newly reachable: 84 historical notes | 17 research papers | 3 diagrams | 2 simulations Figure 15. Semantic Reach Delta Report. The completion report emphasizes new semantic access, not only processing throughput. 49. Next Best Preparatory Work A PSG system MAY rank visible preparation gaps by current-project relevance, staleness, expected semantic yield, cost, and coverage debt. These rankings are scheduling suggestions, not semantic truth and not permission to alter the underlying architecture. Next Best Preparatory Work | The system can surface high-value semantic gaps while leaving the operator in control of what is queued. 1 - HIGH Prosopohermeneia-128 Backfill Current project relevance: HIGH Eligible notes: 614 Existing coverage: 12% 2 - MEDIUM Materials-64 v2 Re-GROOVE Stale projections: 1,441 3 - LOW 2019-2021 Notes Fine Routing Broad GROOVE complete Fine routing: 31% [ QUEUE 1 ] [ QUEUE ALL ] [ EDIT ] Figure 16. Next Best Preparatory Work. The system can surface high-value semantic gaps while leaving the operator in control of what is queued. PSG to Bits Before Tokens Payoff | Preparatory work narrows the future query before expensive source reading begins. BEFORE PSG Query pathBroad retrieval Candidate sources1,200 Prepared coordinatesSparse Token loadLarge AFTER PSG Query path000 -> Routing SK -> 00 Strong candidates18 Original sources opened6 Token loadFocused PREPARATORY WORK -> PERSISTENT SEMANTICS -> QUERY-TIME SAVINGS Figure 17. PSG to Bits Before Tokens Payoff. Preparatory work narrows the future query before expensive source reading begins. PART VIII - WORKED EXAMPLE A new repair Model retroactively reorganizes old notes into a more useful future routing surface. 50. New Model Registration Illustrative scenario: a new semantic instrument named MORPHODYNAMIC_REPAIR-128 is published to represent repair through structured morphological change. The instrument is registered independently of the archive. Registration creates no claim that historical documents belong to it; it merely makes a new interpretive surface available. 51. Historical Eligibility Existing GROOVE projections identify Materials, Biology, Regeneration, Structural Repair, and adjacent branches across a mixed personal and research corpus. The PSG Target Scope Builder selects these neighborhoods, requires existing relevance of at least 0.45, and adds a 5 percent exploratory sample from near-boundary Entries. The resulting Backfill Frontier is 8,744 Entries instead of the full 184,220-Entry corpus. 52. Backfill Execution The job applies MORPHODYNAMIC_REPAIR-128, preserves multifactor route states, factors active routes, generates branch-conditioned descriptions where configured, and proposes relations inside resulting Bundles. Interactive load rises during the day, so the queue pauses automatically and resumes overnight from its saved checkpoint. 53. Expanded Reach When the job completes, 1,301 Entries gain new query-accessible semantic paths, including 84 historical notes that previously had only broad Materials or Biology coordinates. Several Entries now participate in a Biology x Materials x Repair semantic surface. The source artifacts remain unchanged; their discoverability has expanded. 54. Later Query Retrieval Months later, a user asks about biological repair mechanisms that could inspire structural recovery. Bits Before Tokens routes the query through Biology, Regeneration, Materials, and Repair. The newly prepared MORPHODYNAMIC_REPAIR-128 projections intersect the active query frontier, exposing the historical notes before full-text search would have been necessary. Only the strongest source candidates are reopened and read in full. NEW MODEL -> existing GROOVE finds eligible old material -> PSG backfills the new semantic instrument -> old Entries gain new 00 / 000 reach -> later query routes through that prepared reach -> source tokens are spent only on surviving candidates PART IX - FORMAL PRINCIPLES AND CONFORMANCE PSG remains useful only if background enrichment stays bounded, versioned, inspectable, and source-grounded. 55. Normative Principles Table 6. PSG normative principles ID Principle Requirement PSG-L01 Preparatory Work Available low-demand compute SHOULD be used to prepare reusable semantic structure when that work has declared future routing value. PSG-L02 Source Preservation Preparatory processing SHALL NOT rewrite source truth merely to fit a semantic instrument. PSG-L03 Projection Preservation New interpretations SHOULD be stored as versioned projections with lineage rather than silently overwriting prior semantic states. PSG-L04 GROOVE Routes GROOVE Existing semantic projections SHOULD bound later preparatory work when they provide sufficient routing information. PSG-L05 Configurable Passes PSG SHALL NOT require one universal GROOVE pass sequence. PSG-L06 Multifactor Preservation When the applied Routing SK permits multifactor state, PSG SHOULD preserve the combined state before branch factorization. PSG-L07 Interactive Priority Preparatory work SHOULD yield to latency-sensitive interactive work unless explicitly configured otherwise. PSG-L08 Backfill Explicitness Retroactive enrichment SHOULD expose its eligible corpus, current coverage, and Backfill Frontier. PSG-L09 Reach Expansion A PSG Job SHOULD be able to report the semantic reach it added, not merely the number of records processed. PSG-L10 Authority Preservation New semantic routes SHALL NOT silently change source authority, trust, applicability, or permission scope. PSG-L11 Noncanonical Boundary A PSG Projection SHALL remain distinguishable from canonical semantic identity and source provenance. PSG-L12 Resumable Work Long-running PSG Jobs SHOULD checkpoint successful work so pause or interruption does not require wholesale recomputation. PSG-L13 Selective Reopening Full source reopening SHOULD be reserved for passes whose declared grounding requirements or uncertainty justify it. PSG-L14 Semantic Amortization Prepared semantic work SHOULD remain reusable by later routing, comparison, and enrichment operations where the projection is still current and authorized. 56. Failure Modes Table 7. PSG failure modes and corrections Failure mode Why it fails Required correction Blind archive-wide backfill Spends large compute on obviously irrelevant Entries. Use existing GROOVE, explicit scope, or bounded exploratory sampling. One overwritten classification Destroys projection lineage and makes reinterpretation impossible to audit. Persist instrument/version-specific Projections. Background canonical promotion Lets AI interpretation silently become semantic truth. Keep candidate outputs reviewable and noncanonical until governed promotion. One magic readiness score Hides which semantic layers are incomplete or stale. Expose readiness dimensions even if a summary percentage is shown. No pause/resume state Makes opportunistic scheduling unreliable and wasteful. Checkpoint pass and Entry completion state. Scope by folder only Ignores existing semantic topology and increases unnecessary work. Permit semantic targeting by 000, 00, Routing SK coordinate, and missing Projection. Unbounded pass chains Allows background jobs to expand indefinitely. Declare depth, budget, continuation, and failure policies. Authority drift Treats new correspondence as evidence of source authority. Preserve source governance separately from GROOVE projection. Preparatory work blocks user Violates the low-demand operating premise. Apply Interactive Priority and resource ceilings. 57. Conformance Requirements Table 8. PSG v0.1 conformance requirements ID Requirement PSG-C01 Every persisted PSG Job SHALL have stable identity, mode, target scope, and status. PSG-C02 Every applied semantic instrument SHALL be identifiable by stable identity and version. PSG-C03 Every persisted Projection SHALL remain traceable to its source Entry and job/pass provenance. PSG-C04 Target Scope SHALL be inspectable before execution. PSG-C05 A retroactive job SHALL distinguish eligible Entries, already-current Entries, and the Backfill Frontier. PSG-C06 PSG SHALL preserve source versions and SHALL NOT replace substantive source content with generated summaries. PSG-C07 Machine-generated relations or semantic claims SHALL preserve a review state distinct from verified source authority. PSG-C08 A conforming implementation SHALL support pause or safe interruption of long-running jobs. PSG-C09 Permissions SHALL constrain target selection, source reopening, stored projections, and interface disclosure. PSG-C10 New semantic routes SHALL NOT silently alter source authority or context applicability. PSG-C11 A Re-GROOVE operation SHALL preserve or otherwise expose the lineage from prior Projection to replacement/re-evaluation. PSG-C12 Pass order, branching, and stopping behavior SHALL come from job/profile configuration rather than an assumed universal sequence. PSG-C13 Multifactor Routing SK results SHALL preserve the declared combined state when the Routing SK contract permits multiple active routes. PSG-C14 A conforming interface SHOULD expose readiness and reach at a level useful for choosing future preparatory work. PSG-C15 Query-time consumers SHALL be able to reopen the underlying Entry when factual grounding is required. 58. Implementation Roadmap Table 9. Recommended PSG implementation roadmap Phase Build focus Exit criterion 1 - Job spine PSG Job registry, modes, status, target scope, basic queue A manual job can target explicit Entries and persist a run record. 2 - Semantic scope 000/00 and Routing SK selectors, missing-Projection filters Jobs can target semantic neighborhoods without folder-only selection. 3 - Pass runtime Configurable Pass Stack, conditional branches, persistence policies A job can run multiple declared passes and checkpoint each Entry. 4 - Backfill Eligibility analysis, Backfill Frontier, preview, sampling New instruments can selectively backfill historical corpora. 5 - Scheduling Interactive-load policy, pause/resume, resource budgets PSG can safely operate during low-demand periods. 6 - Readiness Coverage dimensions, staleness, projection lineage The system can explain what preparation is missing and why. 7 - Reach metrics Semantic Reach Delta and Bits Before Tokens integration The system can show concrete query-time value created by PSG work. 59. Conclusion A persistent knowledge system should not wait for a question to begin understanding what it already possesses. Preparatory Semantic Grooving makes that principle operational. New Entries can be prepared as they arrive. New Models can be applied to old material. Existing GROOVE can route later GROOVE. Semantic readiness can improve while the system is quiet, and the resulting projections can expand the 000/00 paths available to future queries. The architecture is deliberately conservative about truth. PSG prepares semantic handles; it does not erase sources, invent canonical identity, or decide future intent in advance. Its value is infrastructural: it preserves useful interpretation so later systems can begin from mapped semantic territory instead of reconstructing the same orientation from prose repeatedly. FINAL PRINCIPLE Preparatory Semantic Grooving converts spare compute into future semantic reach. Glossary - Reference Terms Term Definition Backfill Frontier Eligible Entries that do not yet possess the current required Projection for a declared semantic instrument. Continuous Semantic Accretion Ongoing enrichment of a corpus as new Entries and new semantic instruments produce additional persistent projections. Eligibility Surface The bounded set of Entries satisfying a PSG Job's target and semantic eligibility conditions. Forward PSG Preparatory processing of new or materially revised Entries using currently available instruments. Maintenance PSG Preparatory work that repairs missing, stale, or incomplete semantic structure rather than introducing a new instrument. Pass Stack The ordered, conditional, branching, or iterative sequence of semantic passes configured for one PSG Job. Preparatory Routing Use of existing semantic structure to bound and prioritize later preparatory semantic work. Preparatory Semantic Grooving Scheduled, opportunistic, or directed semantic preparation of new or historical Entries to increase persistent readiness and future routing efficiency. Projection Lineage Traceable relationship among source version, semantic instrument version, job/pass configuration, and successive GROOVE Projections. PSG Job A versioned instruction package defining target scope, passes, compute policy, persistence, and completion for one preparatory operation. Query-Ready Knowledge Source-grounded semantic structure sufficient to guide later routing before full source reopening. Re-GROOVE Re-evaluation of existing GROOVE metadata or projections after material source, instrument, or structural change. Retroactive PSG Application of a new semantic instrument to previously ingested Entries. Semantic Amortization Reuse of semantic interpretation performed once across many later operations. Semantic Readiness Multidimensional state describing which useful preparatory semantic layers exist, are partial, stale, or missing. Semantic Reach Delta The newly available discovery paths, Bundle memberships, Model correspondences, and semantic surfaces added by a PSG operation. Semantic Reach Expansion Increase in the future semantic routes through which an existing Entry can be discovered after new Projections are added.