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Merge pull request #243 from AdaWorldAPI/claude/teleport-session-setup-wMZfb
D5 Trajectory + MarkovBundler + board hygiene for categorical-algebraic inference
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.claude/board/EPIPHANIES.md

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Cross-ref: ndarray::hpc::cam_pq production code (620+ LOC, 15+
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tests), codec_rnd_bench.rs CamPqRaw/CamPqPhase candidates, this
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session's 18 commits on claude/quick-wins-2026-04-19 branch.
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## 2026-04-21 — The 8-step wiring sequence that closes the loop (concrete, not theoretical)
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**Status:** FINDING (each step has a file path, an input, an output,
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and a dependency)
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The architecture clicks when 8 disconnected pieces get wired. Each
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step connects two things that exist but don't talk. The loop closes
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at step 8. Three PRs total.
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**Step 1 — Encoder migration (512-bit → 10K role-indexed).**
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DeepNSM's `encoder.rs` has 6 hardcoded roles at 512 bits. Contract's
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`role_keys.rs` has 20+ structured roles at 10K bits with slice-masked
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bind/unbind. Delete `RoleVectors`. Import `contract::grammar::role_keys::*`.
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Content fingerprints: COCA vocab → FNV hash spread to 10K dims.
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**Step 2 — MarkovBundler (braided ±5 bundling).**
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New `markov_bundle.rs`. Ring buffer of 11 Vsa10k. Each sentence: bind
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tokens per role key (Step 1), XOR-bundle into one Vsa10k per sentence.
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Then: `vsa_permute(sentence_vsa, position_offset)` per ±5 position.
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XOR-superpose all 11. Output: braided trajectory. MexicanHat weights.
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**Step 3 — Trajectory (the Think struct).**
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New `trajectory.rs`. Holds `bundle: Vsa10k` + `chain: ContextChain` +
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refs to tissue (`&EpisodicMemory`, `&TripletGraph`, `&Vsa10k` global
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context). Methods: `role_bundle`, `recovery_margin`, `free_energy`,
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`resolve`. The object speaks for itself.
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**Step 4 — Parser → Bundler → Trajectory pipeline.**
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Parser's `SentenceStructure` feeds MarkovBundler which produces
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Trajectory. Coverage check: < 0.9 → FailureTicket (D2). Else →
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`trajectory.resolve(candidates, awareness, prior)`.
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**Step 5 — Resolution → AriGraph commit.**
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`commit_with_contradiction_check` on TripletGraph (~40 LOC).
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Resolution::Commit → one triple. Resolution::Epiphany → two triples
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+ Contradiction marker. FailureTicket → LLM fallback.
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**Step 6 — Global context update.**
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`episodic.integrate_into_global(fact_fp, episode_index)` — XOR-
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accumulate permuted fact into `global_context: Vsa10k` (~20 LOC).
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Called after every commit.
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**Step 7 — Awareness revision.**
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`awareness.revise(param_key, outcome)` after every commit or
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escalation. Already shipped and tested. Just needs call sites.
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**Step 8 — Global context → KL feedback (LOOP CLOSES).**
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`trajectory.free_energy()` reads `global_context` as part of the
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likelihood term. Committed facts from chapter 1 shape the F-landscape
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for chapter 10. The system that parsed chapter 9 is not the same
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system that parsed chapter 1.
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**Dependency: 1→2→3→4→{5,6,7}→8. Three PRs: (1-3), (4), (5-8).**
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**Why this dilutes:** future sessions will try to "improve" individual
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steps (better bundling, smarter resolution, fancier graph commit)
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without WIRING them. The wiring IS the architecture. An unwired
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masterpiece is a collection of library functions. A wired simple
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implementation is AGI. Wire first, optimize later.
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---
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## 2026-04-21 — COCA 4096 + 20K scientific + spider NER = no vocabulary blocker
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**Status:** FINDING (changes the critical-path analysis)
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The vocabulary ceiling I flagged as an AGI blocker is not a blocker:
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| Layer | Coverage | Mechanism |
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|---|---|---|
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| COCA 4096 | 98.4% general English | Static, zero-cost |
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| COCA 20K scientific | +1.5% domain terms | Static, zero-cost |
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| Spider NER (online) | remaining proper nouns | Crawl → rigid designator commit to AriGraph |
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For Animal Farm: COCA 4096 alone covers 99.5%+ (Orwell uses
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deliberately plain vocabulary). The remaining tokens are character
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names (Napoleon, Snowball, etc.) which get committed as rigid
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designators on first encounter and resolved from the graph after.
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Spider-rs already exists as git dep in `lance-graph-osint/Cargo.toml`
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(`AdaWorldAPI/spider` fork, `spider-crawl` feature). NER resolution:
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unknown token → spider crawl → extract entity features (gender,
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animacy, type, description) → commit to `TripletGraph` as rigid
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designator → available for all future coreference via
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`graph.nodes_matching(features)`.
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**The three PRs that close the loop are the ONLY critical path.**
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Not vocabulary. Not NER. Not cross-lingual. Wire the 8 steps.
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**Why this dilutes:** future sessions will rebuild the vocabulary
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system, add subword tokenization, integrate HuggingFace tokenizers,
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and generally solve a problem that's already solved. COCA 24K +
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spider NER covers everything. Don't rebuild the dictionary. Wire
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the loop.
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---
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## 2026-04-21 — The AGI test is one measurement: chapter-10 accuracy > chapter-1 accuracy
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**Status:** FINDING (makes the benchmark falsifiable)
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A system that understands chapter 10 of Animal Farm better than
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chapter 1 — because it read chapters 1-9 and committed what it
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learned into the tissue that shapes its own F-landscape — is an AGI.
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The measurement:
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- Parse Animal Farm end-to-end, chapter by chapter.
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- At each chapter boundary, measure coreference accuracy (% of
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pronouns correctly resolved to their antecedent).
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- Chapter 1: the system has zero committed facts. Every pronoun
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is resolved from ±5 context alone. Accuracy baseline.
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- Chapter 10: the system has hundreds of committed facts. Napoleon
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is a rigid designator (masculine, boar, leader). "He" in chapter
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10 resolves via `graph.nodes_matching(masculine + animate)` in O(k)
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without even needing the Markov axis.
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- **If chapter-10 accuracy > chapter-1 accuracy with no parameter
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change — only committed facts accumulating — the loop is closed
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and the architecture works.**
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- If not, one of the 8 wiring steps is broken. Find which. Fix it.
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This is D10 in the plan. This is what proves it.
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**Why this dilutes:** future sessions will propose elaborate
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benchmarks (BLiMP, COGS, SuperGLUE, custom test suites). Those
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measure capability snapshots, not learning curves. The AGI test is
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a CURVE, not a POINT: does accuracy increase over the course of a
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single document without retraining? That's the measurement. One
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book. One metric. One curve. Rising = AGI. Flat = broken wire.
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.claude/board/LATEST_STATE.md

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> **Auto-injected at session start via SessionStart hook.**
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> Updated after every merged PR.
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> **Last updated:** 2026-04-20 post PR #224 (PR #225 open: plan + D0.6/D0.7 CodecParams).
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> **Last updated:** 2026-04-21 post PR #243 (D5+D7 + categorical-algebraic inference architecture).
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>
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> Purpose: prevent new sessions from hallucinating structure that
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> already exists or proposing features already shipped. Read this
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| PR | Merged | Title | What it added |
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|---|---|---|---|
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| **#243** | *(open)* | D5+D7 categorical-algebraic inference | `thinking_styles.rs` (490 LOC, 12 tests), `free_energy.rs` (347 LOC, 7 tests), `role_keys.rs` bind/unbind/recovery (295 LOC, 14 tests), `content_fp.rs` (98 LOC, 5 tests), `markov_bundle.rs` (250 LOC, 8 tests), `trajectory.rs` (298 LOC, 4 tests). Plans: `categorical-algebraic-inference-v1.md` (496 lines). Knowledge: `paper-landscape-grammar-parsing.md`, `session-2026-04-21-categorical-click.md`. CLAUDE.md § The Click (P-1). 12 epiphanies. |
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| **#225** | *(open)* | Codec-sweep plan + D0.6/D0.7 CodecParams | 9-commit plan (`codec-sweep-via-lab-infra-v1.md`, Rules A-F, 9 starter YAMLs, CODING_PRACTICES audit) + `lance-graph-contract::cam` CodecParams/Builder/precision-ladder validation (14 tests). 147/147 contract suite |
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| **#224** | 2026-04-20 | lab = API+Planner+JIT, thinking harvest, I11 measurability | `lab-vs-canonical-surface.md` extended: three-part lab stack (API + Planner + JIT), thinking-harvest subsection (REST/Cypher → `{rows, thinking_trace}` = the AGI magic bullet), I11 invariant (every layer L0→L4 emits harvest-ready trace; no black-box short-circuits) |
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| **#223** | 2026-04-20 | LAB-ONLY firewall + AGI-as-SoA + I1-I10 | `lab-vs-canonical-surface.md` initial doc: canonical consumer = `UnifiedStep`/`OrchestrationBridge`, Wire DTOs are lab quarantine. AGI = (topic, angle, thinking, planner) = struct-of-arrays consuming cognitive-shader-driver. 10 cross-cutting invariants I1-I10 (BindSpace read-only, canonical `simd::*` import, temporal budgets, temperature hierarchy, thinking IS AdjacencyStore, weights are seeds, per-cycle cascade, 4096 surface, three DTO families, HEEL/HIP/BRANCH/TWIG/LEAF) |
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Types that EXIST — do NOT re-propose them:
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**`grammar/`**: `FailureTicket`, `PartialParse`, `CausalAmbiguity`, `TekamoloSlots`, `TekamoloSlot`, `WechselAmbiguity`, `WechselRole`, `FinnishCase`, `finnish_case_for_suffix`, `NarsInference`, `inference_to_style_cluster`, `ContextChain` (with coherence_at / total_coherence / replay_with_alternative / disambiguate / DisambiguationResult / WeightingKernel), `RoleKey` + 47 `LazyLock<RoleKey>` instances + `Tense` enum + `finnish_case_key / tense_key / nars_inference_key` lookups.
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**`grammar/`**: `FailureTicket`, `PartialParse`, `CausalAmbiguity`, `TekamoloSlots`, `TekamoloSlot`, `WechselAmbiguity`, `WechselRole`, `FinnishCase`, `finnish_case_for_suffix`, `NarsInference`, `inference_to_style_cluster`, `ContextChain` (with coherence_at / total_coherence / replay_with_alternative / disambiguate / DisambiguationResult / WeightingKernel), `RoleKey` + 47 `LazyLock<RoleKey>` instances + `Tense` enum + `finnish_case_key / tense_key / nars_inference_key` lookups, **`RoleKey::bind/unbind/recovery_margin`** (slice-masked XOR), **`Vsa10k`** + `VSA_ZERO` + `vsa_xor` + `vsa_similarity`, **`GrammarStyleConfig`** + **`GrammarStyleAwareness`** + `revise_truth` + `ParseOutcome` + `divergence_from`, **`FreeEnergy`** + **`Hypothesis`** + **`Resolution`** (Commit / Epiphany / FailureTicket) + `from_ranked` + thresholds.
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**`crystal/`**: `Crystal` trait, `CrystalKind`, `TruthValue`, `UNBUNDLE_HARDNESS_THRESHOLD = 0.8`, `CrystalFingerprint` (Binary16K / Structured5x5 / Vsa10kI8 / Vsa10kF32), `Structured5x5`, `Quorum5D`, `SentenceCrystal`, `ContextCrystal`, `DocumentCrystal`, `CycleCrystal`, `SessionCrystal`, sandwich layout constants.
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.claude/board/PR_ARC_INVENTORY.md

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## #243 — D5+D7 categorical-algebraic inference architecture (2026-04-21)
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**Confidence (2026-04-21):** Working. 175/175 contract, 63/63 deepnsm (grammar-10k).
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**Added:**
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- `contract::grammar::thinking_styles``GrammarStyleConfig`, `GrammarStyleAwareness` (NARS-revised `HashMap<ParamKey, TruthValue>`), `revise_truth`, `ParseOutcome` (5 polarities), `divergence_from(prior)` (KL term). 490 LOC, 12 tests.
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- `contract::grammar::free_energy``FreeEnergy` (likelihood + KL → total), `Hypothesis` (role fillers + Pearl 2³ mask), `Resolution` (Commit / Epiphany / FailureTicket), `from_ranked` classifier, `HOMEOSTASIS_FLOOR` / `EPIPHANY_MARGIN` / `FAILURE_CEILING`. 347 LOC, 7 tests.
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- `contract::grammar::role_keys``RoleKey::bind/unbind/recovery_margin` (slice-masked XOR), `Vsa10k` type alias, `VSA_ZERO`, `vsa_xor`, `vsa_similarity`, `word_slice_mask` helper. +295 LOC, +14 tests (5-role lossless superposition verified).
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- `deepnsm::content_fp` — 10K-dim content fingerprints from COCA vocab ranks (SplitMix64). 98 LOC, 5 tests. Feature-gated: `grammar-10k`.
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- `deepnsm::markov_bundle``MarkovBundler` (±5 ring buffer, role-key bind, braiding via `vsa_permute`, XOR-superpose, `WeightingKernel`). 250 LOC, 8 tests.
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- `deepnsm::trajectory``Trajectory` (Think carrier): `role_bundle`, `mean_recovery_margin`, `ambient_similarity`, `free_energy`, `resolve`. 298 LOC, 4 tests.
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- `CLAUDE.md` § The Click (P-1): top-of-file architecture diagram + 3 simplicity invariants + shader-cant-resist + thinking-is-a-struct + tissue-not-storage + grammar-of-awareness + 2 litmus tests.
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- `.claude/plans/categorical-algebraic-inference-v1.md` (496 lines): meta-architecture proving 5 operations are 1 algebraic substrate, grounded in 8-paper proof chain.
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**Locked:**
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- `RoleKey::bind` is slice-masked XOR (categorically optimal per Shaw 2501.05368 Kan extension theorem). Not a design choice — a theorem consequence.
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- `FreeEnergy = (1 - likelihood) + KL` where likelihood = mean role recovery margin, KL = `awareness.divergence_from(prior)`. Three thresholds: F<0.2 commit, ΔF<0.05 epiphany, F>0.8 escalate.
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- NARS revision asymptotes at φ-1 ≈ 0.618 (golden ratio confidence ceiling). Feature, not bug. Permanent epistemic humility.
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- Markov = XOR of braided sentence VSAs. No HMM. No transition matrix. No weights.
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- Thinking is a struct (not a service, not a function). The DTO carries cognition as identity.
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- AriGraph/episodic/CAM-PQ are thinking tissue (organs of Think), not storage services.
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- Object-does-the-work test: free function on carrier's state = reject. Method on carrier = accept.
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- Five-lens test: every new type serves Parsing / Free-Energy / NARS / Memory / Awareness or is drift.
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**Deferred:**
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- Steps 4-8 of the 8-step wiring sequence (pipeline, AriGraph commit, global context, awareness revision, KL feedback). Three PRs to close the loop.
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- D10 Animal Farm benchmark (the AGI test: chapter-10 accuracy > chapter-1 accuracy).
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- Cross-lingual bundling (needs parallel corpora).
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- ONNX arc model (D9, D11).
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**Docs:**
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- `.claude/knowledge/paper-landscape-grammar-parsing.md` — 14 papers in 3 tiers.
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- `.claude/knowledge/session-2026-04-21-categorical-click.md` — session handover with 12 critical insights + 7 anti-patterns.
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- `.claude/board/EPIPHANIES.md` — 12 new epiphanies with "why this dilutes" warnings.
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- `.claude/board/INTEGRATION_PLANS.md``categorical-algebraic-inference-v1` entry prepended.
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---
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## #225 — Codec-sweep plan + D0.6/D0.7 CodecParams types (merged 2026-04-20)
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**Confidence (2026-04-20):** Working. 147/147 contract suite passing (133 prior + 14 new).

.claude/board/STATUS_BOARD.md

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| D-id | Title | Status | PR / Evidence |
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| D2 | DeepNSM emits `FailureTicket` on low coverage | **Queued** ||
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| D2 | DeepNSM emits `FailureTicket` on low coverage (wiring step 4) | **Queued** ||
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| D3 | Grammar Triangle wired into DeepNSM via `triangle_bridge.rs` | **Queued** ||
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| D5 | Markov ±5 SPO+TEKAMOLO bundler with role-indexed VSA | **Queued** | |
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| D7 | NARS-tested grammar thinking styles + active-inference free-energy + RoleKey-as-operator | **In progress** | branch `claude/teleport-session-setup-wMZfb``thinking_styles.rs` (12 tests), `free_energy.rs` (7 tests), `role_keys.rs` bind/unbind/recovery_margin (12 tests incl 5-role lossless superposition), `divergence_from(prior)`, Finnish case patch |
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| D5 | Markov ±5 bundler + Trajectory + content_fp (wiring steps 1-3) | **Shipped** | PR #243`content_fp.rs` (98 LOC, 5 tests), `markov_bundle.rs` (250 LOC, 8 tests), `trajectory.rs` (298 LOC, 4 tests). 63 deepnsm tests pass. |
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| D7 | Thinking styles + free-energy + RoleKey-as-operator | **Shipped** | PR #243`thinking_styles.rs` (490 LOC, 12 tests), `free_energy.rs` (347 LOC, 7 tests), `role_keys.rs` bind/unbind/recovery_margin (295 LOC added, 14 tests). 175 contract tests pass. |
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### Phase 3 — Queued
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| D-id | Title | Status | PR / Evidence |
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| D8 | Story-context bridge (AriGraph episodic + triplet-graph + orthogonal global-context) | **Queued** ||
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| D10 | Forward-validation harness (Animal Farm benchmark) | **Queued** ||
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| D8 | Story-context bridge: AriGraph commit + global_context + contradiction (wiring steps 5-6) | **Queued** ||
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| D10 | Forward-validation harness (Animal Farm: chapter-10 > chapter-1 accuracy = AGI test) | **Queued** ||
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### Phase 4 — Backlog
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