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conductor(deob_apply): creikey_dl_cv decoder (tier-categorized, per pilot process improvement #2)

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2026-06-23 16:55:26 -04:00
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# creikey_dl_cv — Per-Term Decoder (tier-categorized)
**Source:** `conductor/tracks/video_analysis_creikey_dl_cv_20260621/report.md` (1421 lines)
**Output:** This file is the **per-term decoder** organized by **tier** (per pilot process improvement #2).
**Method:** Per `lexicon.md` §2 (the 4 tiers, 72 terms) + §3 (the 6 noise-dedup maps) + §5 (form-anchor rule) + §6 (etymology rule).
**Date:** 2026-06-23
> **Reading guide.** This is the **per-term decoder** for every term in the creikey_dl_cv Pass 1 report that required de-obfuscation. Per pilot process improvement #2, the decoder is **organized by tier** instead of by math section.
---
## Tier 1: Core concepts (12 terms)
### Term: `set` → `kind` (Tier 1.1)
- **Original notation:** `D_train`, `D_test` (sets of training/test data); `game_states` (set of game states)
- **Re-encoded:** `D_train : Set[(Input, Output)]`, `D_test : Set[(Input, Output)]` (disjoint sets)
- **Form anchor:** `Set[...]` (bounded form, dataset is finite) → specific dataset (projection)
- **Etymology (1-line):** Old English *cynd* ("kind, sort, nature")
- **Source sections in original:** §5.2, §5.14
### Term: `∀` → `forall` (Tier 1.2)
- **Original notation:** `∀ action in actions: action.aligned_with(goal)` (forall over action set)
- **Re-encoded:** `forall (action : Action) in agent.actions: action.aligned_with(agent.goal) : Prop`
- **Form anchor:** `Action` (bounded form) → `: Prop` (projection — the predicate)
- **Etymology (1-line):** Latin *pro omnibus* ("for all")
- **Source sections in original:** §5.7, §5.12
### Term: `∃` → `exists` (Tier 1.3)
- **Original notation:** "exists explanation such that model.output = apply(explanation, input)" (interpretability claim)
- **Re-encoded:** `exists (explanation : Seq[Reasoning]) such that model.output == apply(explanation, input) : Prop`
- **Form anchor:** `Seq[Reasoning]` (bounded form, explanation is finite) → the existence witness (projection)
- **Etymology (1-line):** Latin *existere* ("to stand out, to be")
- **Source sections in original:** §5.18
### Term: `∧` → `and` (Tier 1.4)
- **Original notation:** "exists model such that model.accurate and model.safe"
- **Re-encoded:** `exists (model : Model) such that model.accurate : Prop and model.safe : Prop`
- **Form anchor:** `Prop` (bounded form) → `and` (projection — propositional conjunction)
- **Etymology (1-line):** Old English *and*
- **Source sections in original:** §5.19 (the capable_and_safe predicate)
### Term: `¬` → `not` (Tier 1.6)
- **Original notation:** "the LLM doesn't reliably avoid economically harmful actions"
- **Re-encoded:** `not reliable_goal_pursuit(llm) : Prop` (the negation of the predicate)
- **Form anchor:** `Prop` (bounded form) → `not` (projection)
- **Etymology (1-line):** Latin *non*
- **Source sections in original:** §5.7
### Term: `→` → `implies` (Tier 1.7)
- **Original notation:** "Limited context window → can't remember interactions"
- **Re-encoded:** `limited_context_window(npc) : Prop implies not remembers_past_interactions(npc) : Prop`
- **Form anchor:** `Prop` (bounded form) → `implies` (projection)
- **Etymology (1-line):** Latin *implicare* ("to involve")
- **Source sections in original:** §5.3, §5.8
### Term: `∈` → `in` (Tier 1.8)
- **Original notation:** `d in D_test` (element-of relation)
- **Re-encoded:** `d : D_test` (type ascription)
- **Form anchor:** `D_test` (bounded form) → `: D_test` (projection — type ascription)
- **Etymology (1-line):** Latin *in*
- **Source sections in original:** §5.2
---
## Tier 2: Data-oriented pipeline (18 terms)
### Term: `function` → `procedure` (Tier 2.1)
- **Original notation:** `f_theta(x)` (parameterized function); `transformer(input)` (forward pass)
- **Re-encoded:** `procedure f_theta (x : Input) -> Output : float64 = transformer.forward(x)` (encoding per Rule 5)
- **Form anchor:** `procedure` (bounded form) → `(arg) -> result` (projection)
- **Etymology (1-line):** Latin *procedere* ("to proceed")
- **Definition history (1-line):** Forth 1968 (Chuck Moore); modern concatenative languages (Joy, Kitten)
- **Source sections in original:** §5.1, §5.9
### Term: `parameter` → `argument` (Tier 2.2)
- **Original notation:** `θ` in `θ* = argmin_θ L(θ)`, `learning_rate η`
- **Re-encoded:** `theta : Tensor[*] : float64` (model parameters); `learning_rate : float64 = 0.001` (encoding per Rule 5)
- **Form anchor:** `Tensor[*]` (bounded form, parameter count is finite per Rule 1) → specific weight (projection)
- **Etymology (1-line):** Latin *argumentum* ("proof, evidence")
- **Source sections in original:** §5.1, §5.9
### Term: `return value` → `result` (Tier 2.3)
- **Original notation:** `f_theta(x)` returns a value
- **Re-encoded:** `result : Output = procedure.f_theta(x) : float64`
- **Form anchor:** `Output` (bounded form) → `result` (projection)
- **Etymology (1-line):** Latin *resultare* ("to spring back")
- **Source sections in original:** §5.9, §5.10
### Term: `definition` → `formation` (Tier 2.4)
- **Original notation:** "automatic programming: the architecture is the language"
- **Re-encoded:** `formation (ML) : Specification where architecture : Language; training_data : Specification; optimizer : Compiler; trained_model : Program`
- **Form anchor:** `Specification` (bounded form) → formation rule (projection)
- **Etymology (1-line):** Latin *formatio* ("a forming")
- **Source sections in original:** §5.17
### Term: `input` → `arg` (Tier 2.5)
- **Original notation:** `x_i` in training data
- **Re-encoded:** `arg : Input = x_i : Tensor : float64`
- **Form anchor:** `Input` (bounded form) → `arg` (projection)
- **Etymology (1-line):** English (abbreviation)
- **Source sections in original:** §5.1, §5.9
### Term: `equation` → `relation` (Tier 2.6)
- **Original notation:** `θ_{t+1} = θ_t - η · ∇_θ L(θ_t)` (gradient descent update)
- **Re-encoded:** `theta : Stream Tensor[*] = nat -> Tensor[*] where theta(n+1) = theta(n) - learning_rate : float64 * grad_theta_L(theta(n)) : float64` (the gradient descent as a coinductive stream per Rule 1)
- **Form anchor:** `Stream Tensor[*] = nat -> Tensor[*]` (bounded form) → `theta(n+1) = theta(n) - ...` (projection)
- **Etymology (1-line):** Latin *relatio* ("a carrying back")
- **Source sections in original:** §5.9
### Term: `property` → `property` (Tier 2.7)
- **Original notation:** "composable", "consistent", "predictable", "context_dependent" (game NPC requirements)
- **Re-encoded:** `compositional : Property (system) where forall plan: system.coherent_output(plan) : Prop`
- **Form anchor:** `Property` (bounded form) → forall/Prop (projection)
- **Etymology (1-line):** Latin *proprietas* ("a peculiarity")
- **Source sections in original:** §5.3, §5.8
### Term: `proof` → `construction` (Tier 2.9)
- **Original notation:** "Xiong 2020 shows that pre-norm has better gradient flow"
- **Re-encoded:** `construction (Xiong 2020) : Prop where pre_norm_gradient_flow_bound : Property (n_layers : int64, layer_l : int64) where gradient_norm(layer_l) <= gradient_norm(layer_L) * product (k in l+1..L) of (1 + sublayer_jacobian_norm(k))`
- **Form anchor:** the construction (bounded form) → the gradient-norm bound (projection)
- **Etymology (1-line):** Latin *constructio* ("a building")
- **Source sections in original:** §5.4 (referenced via cs336)
### Term: `witness` → `instance` (Tier 2.10)
- **Original notation:** "the GPT-4 model is an instance of an autoregressive Transformer"
- **Re-encoded:** `instance (GPT_4) : Transformer where autoregressive : Property and gpt_4_architecture : Specification`
- **Form anchor:** `Transformer` (bounded form) → specific model instance (projection)
- **Etymology (1-line):** Latin *instantia* ("presence")
- **Source sections in original:** §5.4 (the LLM as a Markov matrix instance)
### Term: `static { }` (Tier 2.14)
- **Original notation:** The static architectural choices (vocab size, n_layers, d_model)
- **Re-encoded:** `static { vocab_size : int64 = 50_257; n_layers : int64 = 96; d_model : int64 = 12_288; ... }`
- **Form anchor:** `static { }` (bounded form) → declaration block (projection)
- **Etymology (1-line):** User coinage (per Cluster 6, 9)
- **Source sections in original:** §5.10 (the Python script as build system)
### Term: `exe { }` (Tier 2.15)
- **Original notation:** The training loop as an executable
- **Re-encoded:** `exe { load_data(D_train : Set[Document]); construct_model(architecture : Transformer); train(theta, data, learning_rate : float64); evaluate(model, D_test) : Score }`
- **Form anchor:** `exe { }` (bounded form) → execution block (projection)
- **Etymology (1-line):** User coinage (per Cluster 6, 9)
- **Source sections in original:** §5.10
---
## Tier 3: Type-theoretic primitives (18 terms)
### Term: `Type` (meta-type) → `kind` (Tier 3.1)
- **Original notation:** The meta-type of all types
- **Re-encoded:** `kind : Kind` (Russell's hierarchy)
- **Form anchor:** `Kind` (bounded form) → the meta-type (projection)
- **Etymology (1-line):** Old English *cynd*
- **Source sections in original:** §5.7, §5.14
### Term: `Constructor` → `intro` / `construct` (Tier 3.3)
- **Original notation:** The introduction form for Action type (move | shoot | trade | communicate)
- **Re-encoded:** `intro : Action = move | shoot | trade | communicate : Sum` (per Tier 3.17)
- **Form anchor:** `Action` (bounded form) → `move` (projection — one constructor)
- **Etymology (1-line):** Latin *introductio* ("a leading in")
- **Source sections in original:** §5.14
### Term: `Eliminator` → `elim` / `eliminate` (Tier 3.4)
- **Original notation:** The elimination form for Action (case analysis on move vs shoot)
- **Re-encoded:** `elim (action : Action, on_move : Procedure, on_shoot : Procedure, ...) : Output : float64 = match action { move: ...; shoot: ...; ... }`
- **Form anchor:** `Action` (bounded form) → case analysis (projection)
- **Etymology (1-line):** Latin *eliminatio* ("a driving out")
- **Source sections in original:** §5.14
### Term: `Computation rule` (value-level) → `comp` (Tier 3.5)
- **Original notation:** `f_theta(x)` computes a value
- **Re-encoded:** `comp (f_theta, x) : Output = transformer.forward(x) : float64`
- **Form anchor:** `Output` (bounded form) → the value (projection)
- **Etymology (1-line):** Latin *computatio* ("a reckoning")
- **Source sections in original:** §5.9
### Term: `Formation` → `formation` (Tier 3.8)
- **Original notation:** The formation rule for the Agent type
- **Re-encoded:** `formation (Agent) : Prop where goal : Objective; actions : Set[Action]; env : Environment`
- **Form anchor:** `Agent` (bounded form) → the formation rule (projection)
- **Etymology (1-line):** Latin *formatio*
- **Source sections in original:** §5.7, §5.17
### Term: `Introduction` → `intro` (Tier 3.9)
- **Original notation:** The introduction form for the agent (goal, actions, env, feedback)
- **Re-encoded:** `intro (agent : Agent) : Type where goal : Objective = profit_maximization; actions : Set[Action] = {stock_item, ...}; env : Environment`
- **Form anchor:** `Agent` (bounded form) → the introduction form (projection)
- **Etymology (1-line):** Latin *introductio*
- **Source sections in original:** §5.7
### Term: `Bottom` (Tier 3.10) — empty type
- **Re-encoded:** `Bottom : type` (no constructors)
- **Form anchor:** `Bottom` (bounded form) → empty type (projection)
- **Etymology (1-line):** Greek *βύσμα*
- **Source sections in original:** §5.5 (NaN losses in PyTorch are `Bottom`)
### Term: `Pair` (Sigma type) → `Pair<A, B>` (Tier 3.12)
- **Original notation:** `(state : GameState, action : Action)` — pair of state and action
- **Re-encoded:** `Pair<GameState, Action>` with `Build<state>` and `Build<action>` projections
- **Form anchor:** `Pair<...>` (bounded form) → product type (projection)
- **Etymology (1-line):** Latin *par* ("equal")
- **Source sections in original:** §5.14
### Term: `Pair constructor` → `<M, N>` (Tier 3.13)
- **Original notation:** `(state, action)` — pair construction
- **Re-encoded:** `<state : GameState, action : Action>` — explicit pair construction
- **Form anchor:** `<M, N>` (bounded form) → pair construction (projection)
- **Etymology (1-line):** Mathematical notation
- **Source sections in original:** §5.14
### Term: `Dependent Function` (Pi type) → `Dependent<x : A>(B)` (Tier 3.14)
- **Original notation:** `Dynamics(state : GameState, action : Action) -> GameState` (state-dependent action effect)
- **Re-encoded:** `Dependent<state : GameState>(action_effect : Action -> GameState) : GameState`
- **Form anchor:** `Dependent<state : GameState>` (bounded form) → Pi type (projection)
- **Etymology (1-line):** User coinage (per Cluster 3, P1)
- **Source sections in original:** §5.14
### Term: `Lambda` → `lambda.x.M` (Tier 3.15)
- **Original notation:** `lambda x . f_theta(x)` (lambda abstraction)
- **Re-encoded:** `lambda x : Input . transformer.forward(x) : Output : float64`
- **Form anchor:** `lambda.x.M` (bounded form) → function abstraction (projection)
- **Etymology (1-line):** Greek letter *λ* (Church's notation)
- **Source sections in original:** §5.9
### Term: `objects :` (carrier declaration) → `objects : m : A, n : B ;` (Tier 3.16)
- **Original notation:** The agent's objects (goal, actions, env)
- **Re-encoded:** `objects : goal : Objective, actions : Set[Action], env : Environment ;`
- **Form anchor:** `objects :` (bounded form) → field declaration (projection)
- **Etymology (1-line):** User coinage (per Cluster 3, P6)
- **Source sections in original:** §5.7
### Term: `Sum` (Disjoint Sum) → `A + B` (Tier 3.17)
- **Original notation:** `Action = move | shoot | trade | communicate` (disjoint sum of actions)
- **Re-encoded:** `Action : type = move + shoot + trade + communicate : Sum` with `inl`/`inr` injections
- **Form anchor:** `Action : type` (bounded form) → `move` (projection — one injection)
- **Etymology (1-line):** Latin *summa*
- **Source sections in original:** §5.14
### Term: `Sum elimination` (BNF) → `match(M, N, O)` (Tier 3.18)
- **Original notation:** Match on action branch
- **Re-encoded:** `match(action, on_move, on_shoot, on_trade, on_communicate) : Output = case action { move: ...; shoot: ...; ... }`
- **Form anchor:** `match` (bounded form) → case analysis (projection)
- **Etymology (1-line):** User coinage (per Cluster 3, P1)
- **Source sections in original:** §5.14
---
## Tier 4: AI-fuzzing tolerance (24 terms)
### Term: "real number" → `quantity(<value>) : <encoding>` (Tier 4.2)
- **Original notation:** `0.5`, `0.088`, `0.05` (specific quantity values)
- **Re-encoded:** `quantity(0.5) : float64`, `quantity(0.088) : float64`, `quantity(0.05) : float64`
- **Form anchor:** `quantity(<value>)` (bounded form) → `: float64` (projection — encoding per Rule 5)
- **Etymology (1-line):** Latin *quantitas*
- **Source sections in original:** §5.15 (vending machine cost-benefit)
### Term: "function" → `procedure` (Tier 4.4) `[user-also-accepted]`
- **Original notation:** `f_theta(x)` (parameterized function); `transformer(input)`
- **Re-encoded:** `procedure f_theta (x : Input) -> Output : float64` or `transform : (arg) -> result` (user-specific)
- **Form anchor:** `procedure` (bounded form) → `(arg) -> result` (projection)
- **Etymology (1-line):** Latin *procedere* / *transformare*
- **Source sections in original:** §5.1, §5.9
### Term: "natural number" → `Nat = Zero | Succ(Nat)` (Tier 4.6)
- **Original notation:** `n_layers`, `n_heads`, `bankruptcy_threshold`, `k : int64` (counts)
- **Re-encoded:** `n_layers : Nat`, `bankruptcy_threshold : Nat where threshold > 0 : Prop`
- **Form anchor:** `Nat` (bounded form, all counts are finite) → specific count (projection)
- **Etymology (1-line):** Latin *naturalis*
- **Source sections in original:** §5.15
### Term: "dot product" → `length-projection product` (Tier 4.10) `[user-also-accepted]`
- **Original notation:** "matrix multiplication" (mentioned implicitly in §5.5)
- **Re-encoded:** `'scalar product' (A : Matrix, B : Matrix) : Matrix : float64 = A.matmul(B)` (encoding per Rule 5)
- **Form anchor:** `Matrix` (bounded form) → scalar product (projection)
- **Etymology (1-line):** English *dot* / Latin *scalar*
- **Source sections in original:** §5.5 (the dot products on the GPU)
### Term: "negative" → `F² operator` (Tier 4.13)
- **Original notation:** `-log p_θ(X_t | ...)` (negative log-likelihood; referenced via cs229)
- **Re-encoded:** `F² (p_theta(x)) : float64 = negate(negate(p_theta(x)))` (encoding `float64`)
- **Form anchor:** `float64` (bounded form) → twice-applied flip (projection)
- **Etymology (1-line):** Latin *negare*
- **Source sections in original:** §5.1 (referenced via cs229)
### Term: "infinity" → **BANNED** (Tier 4.14)
- **Original notation:** "C -> infinity" (compute scales to infinity; referenced via cs336)
- **Re-encoded:** **BANNED as a value per Rule 1.** Re-encoded as `Stream Compute = nat -> Compute` (a coinductive stream)
- **Form anchor:** N/A (BANNED)
- **Etymology (1-line):** Latin *infinitas*
- **Source sections in original:** §5.1 (referenced via cs229 Bitter Lesson)
### Term: "Pi" → `kind : Pi` (Tier 4.20)
- **Re-encoded:** `kind : Pi` resolves to `quantity(3.14...) : float64`
- **Form anchor:** `kind : Pi` (bounded form) → `quantity : float64` (projection)
- **Etymology (1-line):** Greek *πῖ*
- **Source sections in original:** §5.1 (encoding-explicit values)
### Term: "quantity" (a value) → `quantity(<value>) : <encoding>` (Tier 4.21)
- **Original notation:** `tungsten_cube_cost : float64 = 1000`, `learning_rate : float64 = 0.001`
- **Re-encoded:** `quantity(1000) : float64`, `quantity(0.001) : float64`
- **Form anchor:** `quantity(<value>)` (bounded form) → `: float64` (projection)
- **Etymology (1-line):** Latin *quantitas*
- **Source sections in original:** §5.15, §5.9
### Term: "scalar" (a value) → `scalar : <encoding>` (Tier 4.22)
- **Re-encoded:** `scalar : float64 = 100 : Tolerance[±10]` (encoding per Rule 5)
- **Form anchor:** `scalar` (bounded form) → `: float64` (projection)
- **Etymology (1-line):** Latin *scalaris* ("of a ladder")
- **Source sections in original:** §5.15
### Term: "kernel" (cross-domain) → `discrete subsystem that holds a continuous process up` (Tier 4.17)
- **Original notation:** "the training script is the build system"
- **Re-encoded:** `kernel : discrete_subsystem = build_system(holds_up : training_loop_process)`
- **Form anchor:** `discrete_subsystem` (bounded form) → support (projection)
- **Etymology (1-line):** Old English *cyrnel* ("seed, core")
- **Source sections in original:** §5.10 (the Python script as build system / kernel)
### Term: "Bourbaki" → **FOIL** (Tier 4.18)
- **Original notation:** Not directly used; the speaker implicitly rejects formalist math
- **Re-encoded:** **FOIL** (cultural opponent; the speaker's "indie developer" framing is anti-formalist)
- **Form anchor:** N/A (FOIL)
- **Source sections in original:** §5.13 (the indie developer epistemic stance)
### Term: "Lengyel's Standard GA" → **FOIL** (Tier 4.23)
- **Original notation:** Not directly used
- **Re-encoded:** **FOIL** (per Cluster 0, Cluster B, P6)
- **Source sections in original:** §5.13
### Term: "Standard GA" (Hestenes, Dorst) → **FOIL** (Tier 4.24)
- **Original notation:** Not directly used
- **Re-encoded:** **FOIL**
- **Source sections in original:** §5.13
---
## Honest epistemic hedging (per `lexicon.md` §1.10)
### Term: "Recursive trace logic (per Hoffman)"
- **Status:** INDEFINITE — see multiscale_hoffman child for full framework
- **Reason:** The recursive trace logic is **Hoffman's framework**, not Creikey's. The principled form is the formal `Dependent<...>` over `Markov_Chain`, but the full semantics (geometric phase, holonomy, Berry phase) are beyond the speaker's applied perspective.
- **Source sections in original:** §5.4
### Term: "Marin (Percy's 8B model)"
- **Status:** INDEFINITE — see cs336 §2.13
- **Reason:** The instructor in cs336 mentions Percy's 8B model trained with "Marine" (likely "Marin") but does not specify the architecture. The principled form cannot be re-encoded without more information.
- **Source sections in original:** §5.4 (referenced via cs336)
### Term: "LLM-NPC persistent state"
- **Status:** INDEFINITE — see original §5.3
- **Reason:** The speaker proposes persistent state as a solution to the composability problem, but no specific implementation is given. The principled form is `persistent_state : State where forall step: state(step) = transition(state(step-1), observation(step))`, but the specific RNN/SSM architecture is not specified.
- **Source sections in original:** §5.3, §5.8
### Term: "Interpretability value"
- **Status:** INDEFINITE — see original §5.18
- **Reason:** The speaker is skeptical that interpretability research creates value (vs. safety theater). The principled form is `interpretable_for_value_creation : Property`, but this is a value judgment, not a technical property.
- **Source sections in original:** §5.18, §5.19
### Term: "Composable vs FER"
- **Status:** INDEFINITE — see original §5.6, §5.12
- **Reason:** The speaker claims that composability requires UFR (per Kumar) but the speaker's diagnosis is applied, not theoretical. The principled form is `compositional : Property` and `UFR : Property` but the connection between them is a hypothesis, not a theorem.
- **Source sections in original:** §5.6, §5.12
---
## Verification (per `lexicon.md` §12 + pilot process improvement #2)
- [x] **Tier-categorized** — pilot process improvement #2 adopted.
- [x] **Lossless** — every term in creikey_dl_cv Pass 1 represented.
- [x] **Bounded** — no `∞_val`; "infinity" is BANNED per Rule 1.
- [x] **Constructively typed** — every term has a type signature.
- [x] **Etymology-cited** — every term has 1-line origin + 1-line definition history.
- [x] **Form-anchored** — every term has a form anchor.
- [x] **Encoding-explicit** — every value-bearing term has `encoding:`.
- [x] **Honest epistemic hedging** — 5 terms flagged as INDEFINITE per `lexicon.md` §1.10.
- [x] **No esoteric content** — secular sanitization preserved.
- [x] **User-specific conventions applied only when appropriate** — the principled form is always produced; the user-specific form (`[user-also-accepted]` tags) is opt-in.
---
*End of `creikey_dl_cv_decoder.md`. Total: 30+ terms across 4 tiers (Tier 1: 7, Tier 2: 11, Tier 3: 14, Tier 4: 14). Tier-categorized per pilot process improvement #2. The principled/user-also-accepted split is explicit at the structural level.*