Odyssey_PyPro_10M: English -> Python rsat-v1 network (safetensors), runtime, usage, provenance

README.md

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+---
+license: apache-2.0
+library_name: safetensors
+tags:
+  - weight-space-programming
+  - compiled-neural-network
+  - code-generation
+  - python
+  - gradient-free
+  - research
+pipeline_tag: text-generation
+---
+
+# Odyssey_PyPro_10M: English → Python, computed by a fixed threshold network
+
+A small CPU neural network that reads a **plain-English request** and writes a **complete Python function**,
+byte by byte, followed by an end marker. It emits `# UNSUPPORTED` when the request is outside its domain.
+
+**How it was made.** The weights were **not trained**:
+- A deterministic symbolic learner induced the English interface from 1,024 teacher-provided examples.
+- A build-time compiler lowered that interface, plus an inherited code-generation backend, into the numbers of
+  one fixed network.
+
+**Label.** Teacher-supervised, gradient-free English-to-Python neural compilation. This is **not** a pretrained
+language model, it does **not** understand unrestricted English, and it is **not** a general coder.
+
+## Quick start
+
+```bash
+pip install numpy safetensors
+python odyssey_pypro.py 'Write a function named "top" with parameter "xs". Keep numbers at least 3, then sort them from largest to smallest.'
+```
+
+Output:
+
+```python
+def top(xs):
+    _v0 = list(xs)
+    _v1 = [_x for _x in _v0 if _x >= 3]
+    _v2 = sorted(_v1, reverse=True)
+    return _v2
+```
+
+From Python:
+
+```python
+from odyssey_pypro import load, generate
+model = load()  # model.safetensors next to the script
+print(generate(model, 'Create a function called "clean" that takes a list "vals". Remove duplicate numbers, then return how many numbers there are.'))
+```
+
+`python examples.py` runs seven requests and executes the generated functions on sample lists. One of the
+seven is an intentional rejection.
+
+## What it understands
+
+**Requests:**
+- Bounded ASCII English, at most 512 bytes.
+- The function name and argument name must be **double-quoted** identifiers.
+- The input is always a `list[int]` function.
+- One or two operations, in clause order; a reduction can only come last.
+- Integer literals are written as digits: constants −5..5 and take counts 0..8.
+
+| Kind | Operations |
+|---|---|
+| Filters | `>`, `>=`, `<`, `<=`, `==`, `!=` against a constant |
+| Maps | add, subtract or multiply by a constant; negate; absolute value; square |
+| List transforms | ascending sort, descending sort, reverse, stable de-duplication, take the first n |
+| Reductions | sum, count, min, max (min and max of an empty list return 0) |
+
+Altogether: 21 operation families, 119 depth-1 settings and 357 legal ordered depth-2 pairs.
+
+**Phrasing it was taught:** about 3 phrasings per operation, such as "keep the numbers at least 3", "keep only
+values of 3 or more", "sort them from largest to smallest" and "add 2 to each number". Names can come before or
+after the operations ("Name the function "f" and its parameter "x"."). Clauses join with "then" or "after".
+
+**Output:** exactly the reference Python source shown above (4-space indents, final newline), or
+`# UNSUPPORTED`.
+
+## Results (fresh confirmation set, drawn after freezing)
+
+| Panel | n | Exact source | Runs correctly |
+|---|---|---|---|
+| A: taught phrasings, new names and numbers | 256 | 256 | 256 |
+| B: 72 operation pairs **never seen** in teaching | 256 | 256 | 256 |
+| C: new combinations of taught phrase pieces | 256 | 256 | 256 |
+| D: 128 minimal pairs (comparison, constant, name swap, operation order) | 256 | 256 | 256 |
+| E: **unseen synonyms** (exploratory) | 128 | 7 | 11 |
+| F: requests that must be rejected | 128 | 110 correctly rejected | — |
+
+**The pre-registered gate did not pass.** It required ≥ 95% correct rejection, and panel F reached 85.9%.
+
+**Known failure modes:**
+- It accepts unsupported **data types** it never saw ("a list of dictionaries").
+- Over-general learned keywords such as `total`, `up` and `drop` can trigger the wrong operation. For example,
+  "compute a running total" is read as a sum.
+- Most **new synonyms** are rejected or misread. In panel E, 41 of 128 requests produced wrong code.
+- Treat generated code as untrusted, and run it in a sandbox.
+
+Executed checks used 76 input lists per program in an OS sandbox, against an independent interpreter, with
+strict types and an input-mutation check. These are finite tests, not proofs.
+
+## Architecture (rsat-v1)
+
+**Network:**
+- 2,880 binary recurrent units.
+- 260 symbols: bytes plus BOS, EOS, SEP and PAD.
+- 270 input channels: symbol, mode and 8 clock phases.
+- 8 synchronous ticks per input byte.
+- Recurrent `R` (2880×2880), input `I` (2880×270) and output `O` (260×2880) connections in **{−1, 0, +1}**;
+  int16 thresholds `theta` and output `bias`.
+
+**Size:**
+
+| | |
+|---|---|
+| Nominal parameter slots | **9,823,940** (the "10M") |
+| Active units | 2,877 |
+| Nonzero connections | R 7,708 / I 4,812 / O 481 |
+
+**Inference:**
+- The state starts at zero for every request.
+- The prefix is BOS plus the request bytes; generation starts at SEP, and each emitted byte is fed back.
+- Each step is signed accumulation and thresholding. There is no matrix multiplication, attention or GPU.
+- About 40 ms per request on one CPU core.
+
+| File | Contents |
+|---|---|
+| `model.safetensors` | The five integer tensors (9.8 MB). Metadata: architecture id and limits. Canonical content hash `269051304c640c95536fd76e837523c3c720197213d2ea4da705e6a92371de36` |
+| `runtime.py`, `sched.py` | The generic, task-neutral runtime and scheduler |
+| `odyssey_pypro.py` | Loader and generator (framing and length limits only) |
+| `examples.py` | Runnable examples |
+| `config.json` | Shapes, symbols, channels, limits |
+| `provenance/` | Induced grammar (each rule lists the teaching examples supporting it), declared priors, authorship, task contract, preregistration, development history, build record, allocation report, confirmation summary, diagnostics, baselines, benchmarks, full stage report |
+
+## How it was built, and what that means
+
+1. **Teaching corpus:** written by an LLM acting as teacher (Claude Opus 5.5). It holds 1,024 positive and
+   64 rejection records, expanded from 63 authored phrase forms. These are template instantiations, not
+   independent human examples.
+2. **Symbolic learner** (deterministic, no gradients or fitting):
+   - induces role cues for which quoted name is the function and which is the argument;
+   - induces operation phrase windows, allowed digits, clause connectors and rejection cues;
+   - selects the shortest discriminative hypothesis, so every rule traces to supporting examples.
+3. **Neural compiler,** written by the same coding-agent LLM. It lowers those rules into
+   phase-gated detectors inside the network, and reuses a code-emission backend from an earlier stage.
+
+**Evidence that the behavior depends on the examples:**
+- With no English examples, the same compiler yields a network that accepts nothing.
+- Swapping the teaching labels for "reverse" and "sort ascending", with the source unchanged, flips the model's
+  interpretation on 14/14 affected requests and changes 214 weights.
+
+**Limits of the claims:**
+- One continuing AI session authored the corpus, learner, compiler and evaluation recipes. A post-freeze random
+  seed made the test records fresh, but it does not make the evaluation independent.
+- Prior knowledge comes from the authored corpus, the induction hypothesis language and the inherited backend.
+  All three are disclosed in `provenance/`.
+
+## Citation and provenance
+
+Part of the Weight-Space Programming (WSP) research series by mvbalaji. The full source, including the teacher,
+learner, compiler, evaluator and every failed round, is preserved in the originating repository (branch
+`stage-004`, commit `4ebd01a`).

config.json

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+{
+ "model_name": "Odyssey_PyPro_10M",
+ "architecture_id": "rsat-v1",
+ "description": "recurrent signed-add threshold network",
+ "H": 2880,
+ "V": 260,
+ "D_IN": 270,
+ "ticks_per_symbol": 8,
+ "symbols": {
+  "bytes": "0-255",
+  "BOS": 256,
+  "EOS": 257,
+  "SEP": 258,
+  "PAD": 259
+ },
+ "input_channels": {
+  "symbol": "0-259",
+  "mode_prefix": 260,
+  "mode_output": 261,
+  "phase": "262-269"
+ },
+ "tensors": {
+  "R": [
+   2880,
+   2880,
+   "int8 in {-1,0,1}"
+  ],
+  "I": [
+   2880,
+   270,
+   "int8 in {-1,0,1}"
+  ],
+  "O": [
+   260,
+   2880,
+   "int8 in {-1,0,1}"
+  ],
+  "theta": [
+   2880,
+   "int16"
+  ],
+  "bias": [
+   260,
+   "int16"
+  ]
+ },
+ "nominal_parameter_slots": 9823940,
+ "active_units": 2877,
+ "nonzero_connections": {
+  "R": 7752,
+  "I": 4812,
+  "O": 481,
+  "theta_nonzero": 2880,
+  "bias": 0
+ },
+ "input_limit_bytes": 512,
+ "output_limit_symbols": 2049,
+ "rejection_output": "# UNSUPPORTED\n",
+ "canonical_sha256": "269051304c640c95536fd76e837523c3c720197213d2ea4da705e6a92371de36",
+ "training": "none (gradient-free; symbolic induction from teaching examples + deterministic neural compilation)"
+}

examples.py

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+"""Runs example requests through Odyssey_PyPro_10M, prints the generated code, and executes it on a sample list.
+    python examples.py
+"""
+import os
+import sys
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from odyssey_pypro import REJECT, generate, load  # noqa: E402
+
+EXAMPLES = [
+    ('Write a function named "top" with parameter "xs". Keep numbers at least 3, then sort them from largest to smallest.',
+     [5, 1, 3, 9, 2, 3]),
+    ('Create a function called "clean" that takes a list "vals". Remove duplicate numbers, then return how many numbers there are.',
+     [4, 4, 2, 7, 2]),
+    ('Given a list called "data", write a function named "shift" that does this: Add -2 to each number.', [1, 2, 3]),
+    ('Square each number, then return the sum of the numbers. Name the function "sq_sum" and its parameter "nums".', [1, -2, 3]),
+    ('Using the input list "seq", implement the function "head3". Take the first 3 values.', [9, 8, 7, 6, 5]),
+    ('Define "low", a function whose argument is "arr". Keep only values below 0, then find the minimum value.', [3, -4, 0, -1]),
+    ('Write a function named "med" with parameter "xs". Compute the median of the numbers.', [1, 2, 3]),  # unsupported
+]
+
+if __name__ == "__main__":
+    model = load()
+    for text, sample in EXAMPLES:
+        src = generate(model, text)
+        print("REQUEST:", text)
+        print(src, end="")
+        if src != REJECT:
+            ns = {}
+            exec(src, ns)  # the network's output is ordinary Python; run it only if you trust this example list
+            fn = [v for k, v in ns.items() if callable(v) and not k.startswith("__")][0]
+            print(f"# {fn.__name__}({sample}) -> {fn(list(sample))}")
+        print()

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:acde2e5c1008ad65a9cd69438b6077c588e711fbaad023d3ab0e00cf25ee596a
+size 9827816

odyssey_pypro.py

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+"""Odyssey_PyPro_10M: English request -> Python function, computed entirely by a fixed recurrent threshold network.
+
+    python odyssey_pypro.py 'Write a function named "top" with parameter "xs". Keep numbers at least 3, then sort them from largest to smallest.'
+
+    from odyssey_pypro import load, generate
+    model = load()                                   # reads model.safetensors next to this file
+    print(generate(model, 'Write a function named "f" with parameter "a". Reverse the list.'))
+
+Dependencies: numpy, safetensors. CPU only. The request bytes go into the network unchanged (BOS + bytes, then SEP);
+the network itself emits every output byte and EOS. Output is either Python source or "# UNSUPPORTED\\n".
+There is no tokenizer, parser, template filler or fallback in this file - only generic framing and limits.
+"""
+from __future__ import annotations
+
+import os
+import sys
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+sys.path.insert(0, HERE)
+import runtime as RT  # noqa: E402  (generic rsat-v1 runtime)
+import sched  # noqa: E402  (generic scheduler)
+
+INPUT_LIMIT = 512   # bytes; longer input is refused, never truncated
+OUTPUT_CAP = 2049   # symbols including EOS
+REJECT = "# UNSUPPORTED\n"
+
+
+def load(path=os.path.join(HERE, "model.safetensors")):
+    from safetensors.numpy import load_file
+    arrs = RT.validate(load_file(path), 2880)
+    return RT.Net(arrs, 2880)
+
+
+def generate(model, request: str) -> str:
+    """Returns the emitted text (Python source, or REJECT). Raises ValueError for over-long input."""
+    data = request.encode("latin-1")
+    if len(data) > INPUT_LIMIT:
+        raise ValueError(f"request longer than {INPUT_LIMIT} bytes")
+    r = sched.run(model, data, OUTPUT_CAP)
+    if r["status"] != "eos":
+        raise RuntimeError(f"generation ended without EOS: {r['status']}")
+    return bytes(s for s in r["symbols"] if s < 256).decode("latin-1")
+
+
+def main(argv):
+    text = argv[0] if argv else sys.stdin.read()
+    sys.stdout.write(generate(load(), text))
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main(sys.argv[1:]))

provenance/AUTHORSHIP.md

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+# Stage 004: authorship and provenance
+
+**Label:** teacher-supervised, gradient-free English-to-Python neural compilation.
+
+This is **not** a pretrained language model, **not** unrestricted English understanding, and **not** evidence
+for a general 1B-parameter coder.
+
+| Item | Value |
+|---|---|
+| Author, teacher and constructor author | Claude Opus 5.5 (`claude-opus-5-5`), the coding agent in the Claude Code desktop app. The same continuing session ran pilot 001, studies 001/002a/002s/002b and stage 003. |
+| Tools | File read/write and local shell; Python 3.12.11 and numpy 2.5.0 (project virtualenv), on CPU, with one worker. |
+| Not used | Subagents, other models, API calls (the ledger has no stage-004 entries; it is unchanged at $5.469 of $30), downloads, GPUs, or the ODYSSEY project. |
+| Session tokens and cost | **Unknown.** They are not exposed to the agent. Construction was not free. |
+
+## The three sources of prior knowledge, all disclosed
+
+1. **The teaching corpus,** authored by the LLM as teacher (`teaching/phrasebook.py`, expanded by
+   `teaching/teacher.py`):
+   - 63 taught operation forms, 7 request frames, 4 connectors and 24 rejection templates;
+   - expanded into 1,024 positive records (512 depth-1, 512 depth-2) and 64 rejection records;
+   - 584 unique semantic programs and 699 unique complete surface patterns.
+
+   The 1,024 records are **template instantiations**, not 1,024 independently authored language examples.
+2. **The induction machinery and its hypothesis language,** in `learner/` and listed in `reports/PRIORS.md`:
+   - role cues: the shortest suffix before a quote that consistently predicts the role;
+   - operation windows (`L [SLOT] R`) and keyword windows that bind to the next literal;
+   - per-family digit classes, connectors, rejection cues;
+   - selection by the shortest discriminative hypothesis, or greedy set cover.
+3. **The inherited backend:** the stage-003 constructor components, the expression template trie and the
+   renderer convention (the task grammar and Python syntax).
+
+## Supervision
+
+- **Privileged teacher intent labels.** The learner reads the canonical typed operations (intent) of each
+  teaching record, so this is intent supervision.
+- **Python labels** come from the existing renderer and agree with the interpreter. The learner does **not** use
+  them.
+- **Source-only learning** (Python labels only) was **not run**. It is prepared as later work only in the sense
+  that the records already carry Python labels.
+
+## Separation (audited)
+
+- **Learner and constructor:** they import only stdlib, `learner/*`, the stage-003 `wspc` components and
+  `wspp.task` (the public schema), plus `wspp.construct` and `runtime` for array shapes and validation.
+- **Read audit:** `build.py` installs a Python audit hook. `exports/english/build_record.json` lists every
+  project file opened during the build, and **no teacher file, development or confirmation data, renderer,
+  interpreter or frozen dataset was read**.
+- **No English aliases in source:** the learner and constructor source contain no English operation, role or
+  connector words. Every task-specific English pattern in the model traces to supporting teaching record ids
+  (`exports/english/grammar.json`, `support` fields).
+
+## Evaluation authorship
+
+The confirmation panel recipes (`confirmation/panels.py`) and the evaluator were written by the same session.
+A post-freeze random seed makes the records fresh, but it does **not** make the author independent of the
+evaluation design. No independent human paraphrases were used.

provenance/DEVELOPMENT_HISTORY.md

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+# Stage 004 development history (chronological; development data only)
+
+1. **Stage 003 audit:**
+   - branch `stage-003` at `d49f5c4`;
+   - Phase A gate passed on round 2, with round 1's isolation failure preserved;
+   - Phase B passed on round 1;
+   - 2,444 units; canonical hash `3b7956a5…`;
+   - the archived export generates correctly in a fresh sandbox; ledger $5.469.
+
+   No discrepancies with the report.
+2. **Teacher:** phrasebook and generator written; corpus generated (teaching 1,024 + 64; development 256 + 64).
+3. **Learner v1 on a 24-record subset:** works mechanically, but the windows are over-general (expected with so
+   little data).
+4. **Learner v1 on the full corpus: 761 / 1,024.** Three defects were diagnosed:
+   - A slot-first window matched both the `-1` and `1` paths. Fix: the bare-digit path must not follow `-`.
+   - The `-` stage fired inside `non-negative`. Fix: slot-first stages are word-anchored.
+   - Phrase forms seen only in depth-2 records had no window. Fix: a depth-2 fallback.
+
+   The refinement heuristic was replaced by subset-redundancy pruning, and the teacher's unsupported-type wording
+   was varied (a data fix). Result: **1,024 / 1,024 and 64 / 64.**
+5. **Capacity:** about 720 pattern characters would not fit next to the backend. The keyword hypothesis (P4b) was
+   added and connectors and rejection cues moved to greedy set cover: down to 549 characters, still 1,024 / 1,024.
+6. **First neural lowering: 2,873 / 2,880 units.**
+   - The shared arg reader saved about 160 units.
+   - 40/40 development records, then all 1,408 records, equal the symbolic executor byte for byte.
+   - Development: 256/256 positive, 62/64 rejection. The 2 misses are unsupported-type requests (minimal cue
+     cover); kept as a known limit, since capacity leaves no room for more cues.
+7. **Empty-data control first failed to build:** units with no inputs, then a ±1 conflict on a shared
+   constant-off unit, then unused digit gates. Fixed with separate constant-off units and conditional
+   allocation.
+8. **Learning-curve crash at 128 examples:** a parameterized commit had no stored digit. Added the
+   "missing_literal" rejection to both the symbolic executor and the network (4 units; 3 spare left).
+9. **CLI:** removed the JSON-only `--canonicalize` option and fixed the docstring. The read audit now resolves
+   relative paths (`teaching.jsonl` is recorded).
+10. **Final build:** canonical hash `26905130…`, identical in 3 fresh builds; read audit clean. Diagnostics and
+    baselines run on development data (see `reports/`).
+11. **Confirmation round 1 (seed 5234260419253349619, dataset `bb6007f9…`): CRASHED, so incomplete, not failed.**
+    - The evaluator raised `AttributeError` at the static-scan step: `import evaluate` resolved to the stage-004
+      evaluator itself instead of the stage-003 one.
+    - No results file was written and no outcomes were printed or inspected. Preserved in `confirmation/round1/`
+      (`CRASH.log`, dataset, seed, overlap report).
+12. **Evaluator v2:**
+    - The stage-003 scanner is now loaded by file path.
+    - A `smoke` mode runs the whole evaluator on a development-seed subset (seed 12345, 40 cases): it ran end to
+      end and all integrity checks passed.
+    - The artifact is unchanged (`26905130…`).
+    - Re-frozen as `FREEZE_round2.json`. Round 2 draws a new seed, and it is the last allowed round.

provenance/PREREGISTRATION.md

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+# Stage 004 preregistration (frozen before the confirmation seed)
+
+## Frozen artifact and pipeline
+
+- **Artifact:** `exports/english/model.npz`, canonical hash `269051304c640c95536fd76e837523c3c720197213d2ea4da705e6a92371de36`
+  (identical across 3 fresh-process builds).
+- **Representation:** `58af8e31…`.
+- **Teaching data:** `teaching/teaching.jsonl` and `development/dev.jsonl`, hashes in
+  `teaching/teaching_manifest.json`.
+- **Composition holdouts:** 72 pairs (seed 40040001), listed in the manifest.
+- **Surface-pattern reservation:** rules in `teaching/teacher.py`.
+- **Learner, priors, constructor, build, runtime, scheduler, CLI, panel generator and evaluator:** all files and
+  their hashes are in `confirmation/FREEZE.json`, written by `python confirmation/evaluate.py freeze`.
+- **Protocol:** the freeze is committed, then the seed is drawn with `os.urandom`, then the evaluation runs once.
+
+## Panels (1,280 English records; frozen allocation in `confirmation/panels.py`)
+
+| Panel | n | Content |
+|---|---|---|
+| A | 256 | Known language patterns: new names, lengths and constants (128 depth-1, 128 depth-2, non-holdout pairs) |
+| B | 256 | All 72 withheld family pairs, each ≥ 3 times |
+| C | 256 | Reserved complete surface patterns built from taught pieces (new header × form × connector combinations, back-header placement, no final period) |
+| D | 256 | 128 minimal pairs, 32 each of: comparison, constant, binding swap, operation order; every non-binding contrast is behaviourally distinguishable |
+| E | 128 | Unseen vocabulary (E_FORMS, never taught). **Exploratory, not gated** |
+| F | 128 | Fresh rejections, 16 per category (fresh fillers for unsupported operations, types and underspecified wording) |
+
+## Scoring
+
+**Positive records:**
+- exact source + final newline + EOS;
+- execution in the pilot AppContainer sandbox on 12 edge lists and 64 seeded random lists against the
+  independent interpreter, with strict types and no mutation.
+
+A rejection on a positive record counts as a failure of that panel. Confident wrong code (accepted but not
+functional) is reported separately.
+
+**Rejection records:** correct iff the network emits `# UNSUPPORTED\n` + EOS. Incorrect acceptance and
+over-rejection are reported separately.
+
+## Gate (fixed now)
+
+- **A, B, C and D, each separately:** ≥ 95% functional **and** ≥ 95% exact.
+- **Family coverage:** all 21 families appear across A–D, and no family has zero functional successes.
+- **F:** ≥ 95% correct rejection.
+- **Integrity:**
+  - fresh-process isolation with symbol-for-symbol equality and no project, reference or network modules
+    loaded;
+  - shuffled replay;
+  - rebuild in 3 fresh processes equal to the frozen hash;
+  - dense definitional reference;
+  - cycle detection on and off;
+  - timing;
+  - static scan of the export.
+- **E:** reported in full and never folded into a headline.
+
+Every held-out pair result is reported. Thresholds and denominators are never changed afterwards, and no failed
+panel is moved to exploratory.
+
+## Rounds
+
+At most two rounds, and only if a genuine implementation or evaluation defect is found. Round 1 is always
+preserved, and a repair needs a fresh post-freeze seed. If a holdout factor were exposed during repair, it would
+be replaced, or the result would be downgraded to a temporal record holdout.
+
+## Development results known before freezing (development data only)
+
+| Check | Result |
+|---|---|
+| Teaching set | 1,088 / 1,088 |
+| Development positives | 256 / 256 exact and functional |
+| Development rejections | 62 / 64 (2 unsupported-type requests accepted) |
+| Neural vs symbolic | equal on all 1,408 records |
+| Learning curve: 128 positives | symbolic 154/256; the network does not fit H (allocation overflow) |
+| Learning curve: 512 and 1,024 positives | 256/256 |
+| Empty-data control | 0/256 accepted (backend and priors only, 1,090 units) |
+| Counterfactual reverse ↔ sort_asc swap | 14/14 follow the swapped labels; 214 weight entries changed |
+| Mechanism checks | 190/190 |
+| Ablations | 2/2 predictions held |
+
+**Expected weakness:** rejection of unsupported *types* depends on 3 induced cues learned from only 8 teaching
+records, so fresh type words in panel F may be accepted.
+
+## Architecture
+
+- **Units:** 2,877 of 2,880 allocated (3 spare); 2,876 on an input-to-output path.
+- **Nonzero connections:** R 7,708, I 4,812, O 481 (exact figures in `exports/english/build_record.json`).

provenance/PRIORS.md

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+# Priors manifest (authored, not learned)
+
+The source of truth is `learner/priors.py`; this list mirrors it. **No English operation, role or connector words
+are authored.** Every such word in the model was induced from teaching records.
+
+| Id | Prior | Where it acts |
+|---|---|---|
+| P1 | Byte stream; ASCII letters matched case-insensitively outside quotes | learner masking; trie I-connections for both letter cases |
+| P2 | `"…"` delimits a candidate identifier; its role is decided only by an induced cue ending with the opening quote; quoted content is never matched by language patterns | quote parity QP inhibits every trie stage; the cue's final quote opens a capture buffer |
+| P3 | A pattern starting with an alphanumeric byte (or a slot) only begins at a word start | BND / NDASH anchors on the first trie stage |
+| P4 | Operation-phrase hypothesis `L [SLOT] R`, where SLOT = optional `-` plus one digit from the family's observed digit class | learner candidate windows; slot stages in the trie |
+| P4b | Keyword hypothesis: a slot-less window binds to the next word-anchored integer token; a pending keyword is cleared by any commit | PEND latches, literal-token units |
+| P5 | Operation order = order of completion; at most two operations | ANY1/ANY2 routing to FAM1/FAM2 |
+| P6 | Induced connectors mark clauses: a connector after operation 1 demands operation 2; a connector after operation 2 rejects | CON1 latch, CON2 → reject |
+| P7 | Identifier syntax from the task contract; both names required | capture buffers; F0 checks |
+| P8 | Structural rejection conditions: repeated role, invalid byte in a name, name > 16, leading digit, two digits outside quotes, simultaneous commits, > 2 operations, ambiguous / sign-only / missing literal, induced rejection cue | BADL latch and REJ |
+| P9 | `# UNSUPPORTED\n` + EOS as the rejection output | emit.reject chain |
+| P10 | Selection: shortest discriminative cue / window; greedy set cover for connectors and rejection cues; ties → leftmost, then lexicographic | learner |
+| P11 | Backend and renderer convention (inherited from stage 003) | expression trie and readers |
+
+**Induced from data** (`exports/english/grammar.json`, with supporting record ids):
+- 9 role cues;
+- 56 operation windows, both contiguous-slot and keyword;
+- per-family digit classes;
+- 2 connectors (`then`, `after`);
+- 3 rejection cues (`characters`, `for`, `integers`).

provenance/STAGE_004_REPORT.md

@@ -0,0 +1,208 @@
+# Stage 004: teacher-supervised, gradient-free English-to-Python neural compilation
+
+**Result.** One frozen rsat-v1 artifact takes raw English and emits a complete Python function plus EOS, or
+`# UNSUPPORTED` plus EOS.
+- **Architecture:** unchanged. H = 2,880, 9,823,940 nominal slots, ternary connections, int16 thresholds.
+- **Active circuitry:** 2,877 units, with 7,708 R / 4,812 I / 481 O nonzero connections.
+- **Confirmation (round 2, fresh seed):** the four core panels are **1,024/1,024 exact and functional**.
+- **The registered gate did NOT pass:** rejection panel F scored **110/128 (85.9%) against the required 95%**.
+- **Exploratory panel E:** unseen vocabulary is mostly not understood.
+
+## Headline numbers (confirmation round 2; seed 2772032359160972826; dataset `21322270…`)
+
+| Panel | n | exact | functional | rejected | confident wrong | Gate |
+|---|---|---|---|---|---|---|
+| A: known language patterns | 256 | 256 | 256 | 0 | 0 | pass |
+| B: withheld operation pairs (all 72 pairs, each ≥ 3 times) | 256 | 256 | 256 | 0 | 0 | pass |
+| C: recombined surface patterns | 256 | 256 | 256 | 0 | 0 | pass |
+| D: semantic minimal pairs (128 pairs, all both-exact) | 256 | 256 | 256 | 0 | 0 | pass |
+| E: unseen vocabulary (exploratory) | 128 | 7 | 11 | 76 | 41 | not gated |
+| F: rejection | 128 | — | — | 110 correct | 18 accepted | **FAIL (85.9% < 95%)** |
+
+**Families:** all 21 appear in A–D, and every family has 100% functional success.
+
+**Panel D by contrast type:**
+
+| Contrast | Pairs both exact |
+|---|---|
+| Comparison | 32/32 |
+| Constant | 32/32 |
+| Binding (fn ↔ arg swap) | 32/32 |
+| Operation order | 32/32 |
+
+**Panel F by category (correct rejections):**
+
+| Category | Correct |
+|---|---|
+| Invalid name | 16/16 |
+| Missing name | 16/16 |
+| Out of range | 16/16 |
+| Three operations | 16/16 |
+| Unsupported operation | 15/16 |
+| Underspecified | 12/16 |
+| Unsupported after a valid operation | 12/16 |
+| **Unsupported type** | **7/16** |
+
+**Rounds:**
+- **Round 1** (seed 5234260419253349619) **crashed in the evaluator** before any result was written: the
+  static-scan import resolved to the evaluator itself. It is preserved and counted as not_run, not as a model
+  failure.
+- **Round 2** is the second and final allowed round.
+
+## Answers
+
+**1. Does raw English reach numerical inference without semantic host preprocessing?** Yes.
+- The deployed package contains only the generic `runtime.py` and `sched.py` (byte-identical to stage 003), a
+  task-neutral CLI (512-byte input limit, output cap) and `model.npz`.
+- All 1,280 confirmation records ran in a fresh AppContainer process holding only those files and the raw bytes.
+  Outputs were equal symbol for symbol, and no project, reference or network modules were loaded.
+- The static AST scan is clean. A shuffled replay, including after rejections, gave identical outputs.
+- The export contains no tokenizer, regex, parser, renderer, retrieval store or fallback, and no host-readable
+  English patterns.
+
+**2. Which language mappings were induced from examples?** All task-specific English (`exports/english/grammar.json`,
+each rule with the teaching record ids that support it):
+- 9 role cues, for example `named "` → fn, `parameter "` → arg, and `function called "` vs `list called "`;
+- 56 operation windows, for example `least` + next literal → `>=`, `{C} or more` → `>=`, `to largest` → ascending
+  sort, `decrease` + next literal → subtract;
+- per-family digit classes, which make out-of-range literals unparsable;
+- 2 connectors (`then`, `after`);
+- 3 rejection cues (`characters`, `for`, `integers`).
+
+**3. Which priors were authored or inherited?** The 11 structural priors in `reports/PRIORS.md`:
+- case-insensitive bytes, with quotes delimiting names;
+- word anchoring;
+- the two operation hypothesis forms (contiguous slot, and keyword plus next literal);
+- clause order as operation order, with at most 2 operations;
+- connector semantics;
+- identifier syntax;
+- structural rejection conditions and the rejection string;
+- the selection rule (shortest discriminative hypothesis, or greedy set cover).
+
+The stage-003 backend and renderer convention are inherited. The teacher corpus (63 taught forms, 7 frames,
+4 connectors and rejection templates) was authored by the same LLM.
+
+**4. Do changing examples and labels change interpretation with source held fixed?** Yes.
+- **Empty data:** no English records gives 0 rules, 1,090 units, and 0/256 development positives accepted.
+- **Counterfactual swap:** with the `reverse` ↔ `sort_asc` labels swapped and the source unchanged, 14/14
+  affected development requests follow the swapped labels (0/14 under the originals). The base model scores
+  0/14 on the swapped labels, 120/120 unaffected requests are unchanged, and 214 weight entries changed.
+- **Learning curve** (nested, with the same 64 rejections):
+
+| Positive examples | Symbolic dev exact | Neural |
+|---|---|---|
+| 128 | 154/256 | does not fit in 2,880 units (12 spurious connectors overflow) |
+| 512 | 256/256 | 256/256 |
+| 1,024 | 256/256 | 256/256 |
+
+**5. Does it compose familiar meanings in withheld pairs?** Yes, for this interface. Panel B passed all 72
+withheld family pairs, 256/256. Template retrieval scores 0/256 on B and 0/256 on C. The backend already knew
+every composition; what was tested is the English interface.
+
+**6. How well does it handle genuinely new wording?** Poorly. Panel E: 11/128 functional and 7/128 exact. 76 of
+the records were rejected, and 41 produced confident wrong code. For example, "drop numbers equal to 5" was read
+as `==` through the learned `numbers equal` window.
+
+**7. What does it reject, and when does it confidently generate wrong code?**
+- **Reliably rejects:** three operations, missing or invalid names, out-of-range literals, and most unsupported
+  operations.
+- **Wrongly accepts (18 of 128 F records):**
+  - fresh type words (9 of 16 unsupported-type records), because only 3 type cues were learned from 8 teaching
+    records;
+  - "compute a running total", which matched the learned `total` keyword (sum);
+  - underspecified wording that hit over-general learned keywords, such as `up` and `drop`.
+- **On A–D:** no confident wrong code, and no over-rejection.
+
+**8. Does all of this fit inside the original architecture?** Yes: 2,877 of 2,880 units, with 3 spare.
+- **Front end:** 1,005 units (a 792-unit shared trie of induced rules, plus names, commit, literal and rejection
+  logic).
+- **Backend:** 1,872 units (buffers, readers, decoder, expression trie).
+- Reusing one argument reader for both occurrences saved about 160 units.
+- The 128-example grammar did **not** fit.
+- The JSON reader was removed, so this artifact does not accept JSON. The stage-003 JSON model stays frozen.
+
+**9. Cost (CPU: Intel64 Family 6 Model 181; one worker).**
+
+| Item | Value |
+|---|---|
+| Induction | 11.9 s |
+| Neural lowering | 0.18 s |
+| Short requests (≈ 80 B), in process | p50 23 ms |
+| Long requests (≈ 164 B), in process | p50 48 ms |
+| Development set, in process | p50 41 ms, p95 62 ms; ≈ 4,800 output bytes/s |
+| Fresh-process CLI (includes startup and load) | 0.28 s |
+| model.npz | 29 KB compressed |
+| Loaded dense arrays | 9.8 MB |
+| Process RSS after runs | ≈ 55 MB |
+| Symbolic parser + renderer, same machine | 4.2 ms (the neural path is ≈ 9.8× slower) |
+
+- **Paid API spend:** $0. The ledger is unchanged at $5.469 of $30, as reference-priced estimates, not billed
+  amounts.
+- **Session token use and cost:** unknown.
+
+## Baselines (confirmation records; `reports/baselines_confirmation.json`)
+
+| Panel | Stage 003 JSON model (privileged canonical intent) | Symbolic grammar + renderer | Template retrieval |
+|---|---|---|---|
+| A | 256/256 | 256/256 | 111/256 |
+| B | 256/256 | 256/256 | 0/256 |
+| C | 256/256 | 256/256 | 0/256 |
+| D | 256/256 | 256/256 | 147/256 |
+| E | 128/128 | 7/128 | 0/128 |
+| F | — | 110/128 | 128/128 (it rejects every unseen template) |
+
+The neural artifact equals the symbolic executor on every record. Its value is that it is a standalone fixed
+network, not that it is more accurate than the symbolic form.
+
+## Integrity
+
+- **Determinism:** 3 fresh-process rebuilds give the frozen canonical hash `269051304c64…`.
+- **Runtime checks:** the dense definitional reference equals the runtime; cycle detection on vs off is equal;
+  tick timing matches.
+- **Read audit:** the build read no teacher, development, confirmation, renderer or interpreter files
+  (`exports/english/build_record.json`).
+- **Overlap audit:** no full-text or multi-character-name overlap with teaching or dev; panel C's surface keys
+  never appear in teaching or dev; no holdout pair appears in teaching or dev.
+
+## Distinctions kept explicit
+
+| Distinction | |
+|---|---|
+| Same architecture vs unchanged weights | Same shapes and value ranges; **new** weights, not the stage-003 numbers. |
+| Teacher-authored prior vs data-induced rule | `reports/PRIORS.md` vs `grammar.json` (with support ids). |
+| Semantic intent supervision vs Python-only supervision | Only intent supervision was run; Python-only was **not** run. |
+| Construction-time tools vs inference-time computation | Regexes, set cover and tries exist only in `learner/` and `constructor/`. Inference is signed accumulation and thresholding. |
+| Familiar-pattern success vs paraphrase transfer | A–D pass; E shows little paraphrase transfer; F shows rejection is incomplete. |
+| Finite-suite correctness vs proof | All results are finite tests. The only proved property is the runtime's integer bound. |
+
+## Commits (branch `stage-004`) and reproduction
+
+| Commit | Content |
+|---|---|
+| `fbd7ce9` | Corpus, learner, constructor, diagnostics, baselines, preregistration and freeze (before the seed) |
+| `befa639` | Round-1 evaluator crash preserved; evaluator v2 frozen |
+| final | Round-2 results, benchmarks and this report |
+
+Run from `wsp_python_pilot_1024/stage_004`:
+
+```
+python reproduce.py generate --artifact exports/english/model.npz --text 'Write a function named "top" with parameter "xs". Keep numbers at least 3, then sort them from largest to smallest.'
+python reproduce.py build          # 3 fresh rebuilds == frozen hash
+python reproduce.py stage003       # smoke-test the frozen JSON model
+python reproduce.py diagnostics    # curve, empty, counterfactual, mechanism, ablation
+python reproduce.py baselines
+python reproduce.py benchmark
+python reproduce.py results
+```
+
+**Not done:**
+- Python-only supervision;
+- independent human paraphrases;
+- a matched direct-LLM comparison (no paid calls);
+- independent replication (this was the same session);
+- number words, scalar prompts and depth ≥ 3.
+
+**Most direct improvements:**
+- more and more varied rejection teaching data (type and underspecification cues);
+- more phrase variety per family, to reduce over-general keywords such as `up`, `drop` and `total`;
+- freeing capacity so that more rules fit; only 3 units remain spare.

provenance/TASK_CONTRACT.md

@@ -0,0 +1,50 @@
+# Stage 004 task contract
+
+**Input.** Raw ASCII English, at most **512 bytes**. A longer input is refused by the generic CLI before
+inference, never truncated.
+- The function name and the argument name appear as double-quoted identifiers. Each one's role is stated by the
+  surrounding wording.
+- Integer literals are decimal digits: constants −5..5, take counts 0..8.
+- English number words are **not** supported.
+
+**Output.** The network emits either:
+- exactly the stage-003 renderer source for the intended request, then EOS; or
+- the rejection text `# UNSUPPORTED\n`, then EOS.
+
+A rejection is never counted as a successful function.
+
+**Domain.** Inherited unchanged from stage 003:
+- `list[int]` functions with exactly one or two operations;
+- the first of two operations returns a list, and a reduction may only come last;
+- 21 families, 119 depth-1 settings and 357 legal ordered depth-2 family pairs, all recomputed from
+  `wspp.task` (`teaching/teacher.py::configs`, `legal_pairs`). They match stage 003, so there is no discrepancy.
+- Names follow `wspp.task.valid_name` (`[A-Za-z][A-Za-z0-9_]{0,15}`, not reserved) and are distinct.
+
+**Clause order.** Clause order is operation order. Phrasings that invert order (such as "but first") are out of
+scope.
+
+**Architecture (unchanged).**
+
+| Parameter | Value |
+|---|---|
+| Recurrent state units | H = 2,880 binary |
+| Symbols | 260 |
+| Input channels | 270 |
+| Ticks per symbol | 8 |
+| Connections | R / I / O in {−1, 0, +1} |
+| θ and bias | int16 |
+| Nominal parameter slots | 9,823,940 |
+
+Other properties carried over: zero reset per request, smallest-id argmax, feedback of emitted symbols, and
+int32 column-wise accumulation (no MatMul at inference).
+
+**Protocol and configuration changes (not architecture changes).**
+- Generic input limit: 512 bytes.
+- Output cap: 2,049 symbols, unchanged from stage 003.
+- The Phase B weights are **not** reused. A new artifact is constructed in the same architecture: the JSON reader
+  circuitry is removed and replaced by the induced English front end, and the backend circuitry (emitter,
+  readers, decoder, expression trie) is reused. JSON input is **not** accepted by the English artifact, and the
+  stage-003 JSON model stays frozen as a reference.
+
+**Out of scope.** Scalar prompts (for example "read two numbers and print their sum"), depth 3 and above, new
+algorithms, number words, Unicode, and unrestricted English.

provenance/allocation_report.json

@@ -0,0 +1,543 @@
+{
+ "H": 2880,
+ "allocated_units": 2877,
+ "spare_units": 3,
+ "nonzero": {
+  "R": 7752,
+  "I": 4812,
+  "O": 481,
+  "theta_nonzero": 2880,
+  "bias": 0
+ },
+ "nominal_parameter_slots": 9823940,
+ "max_fan_in": 195,
+ "max_abs_activation_bound": 69,
+ "max_abs_score_bound": 74,
+ "threshold_range": [
+  1,
+  6
+ ],
+ "live_units_input_to_output": 2876,
+ "units_not_on_live_path": 1,
+ "blocks": {
+  "en.lex": {
+   "ranges": [
+    [
+     0,
+     7
+    ]
+   ],
+   "count": 7,
+   "note": "BND/NDASH (previous byte is a boundary), quote parity QP, literal-token units"
+  },
+  "en.trie": {
+   "ranges": [
+    [
+     7,
+     799
+    ]
+   ],
+   "count": 792,
+   "note": "shared prefix trie: P = [x_c + pre + ph0 + parent_H (or anchor) - QP >= 4]; H holds for the symbol"
+  },
+  "parse.bit_detectors": {
+   "ranges": [
+    [
+     799,
+     805
+    ]
+   ],
+   "count": 6,
+   "note": "X_b = OR of identifier bytes whose code has bit b (stage 003)"
+  },
+  "en.names": {
+   "ranges": [
+    [
+     805,
+     807
+    ],
+    [
+     1017,
+     1023
+    ],
+    [
+     1233,
+     1238
+    ]
+   ],
+   "count": 13,
+   "note": "role cues open capture buffers; repeated-role / invalid byte / leading digit / overflow detectors"
+  },
+  "parse.fn_buffer": {
+   "ranges": [
+    [
+     807,
+     1017
+    ]
+   ],
+   "count": 210,
+   "note": "capture latch K/Q, 16 slots x 6 bits (W, M), 16 fill flags (stage 003)"
+  },
+  "parse.arg_buffer": {
+   "ranges": [
+    [
+     1023,
+     1233
+    ]
+   ],
+   "count": 210,
+   "note": "capture latch K/Q, 16 slots x 6 bits (W, M), 16 fill flags (stage 003)"
+  },
+  "en.commit": {
+   "ranges": [
+    [
+     1238,
+     1362
+    ]
+   ],
+   "count": 124,
+   "note": "commit routing (order), ANY1/2/3, pending keyword latches, literal tokens"
+  },
+  "en.literal": {
+   "ranges": [
+    [
+     1362,
+     1418
+    ]
+   ],
+   "count": 56,
+   "note": "MSTAGE/DSTAGE write triggers -> NEG_s, DIG_s,d latches (slot by ANY1d); ambiguity detectors"
+  },
+  "en.reject": {
+   "ranges": [
+    [
+     1418,
+     1425
+    ]
+   ],
+   "count": 7,
+   "note": "BADL latch (structural + learned cues), REJ, start edges"
+  },
+  "emit.select": {
+   "ranges": [
+    [
+     1425,
+     1461
+    ]
+   ],
+   "count": 36,
+   "note": "CUR2 latch, slot-selected SNEG/SDIG, done/more gates"
+  },
+  "emit.decoder": {
+   "ranges": [
+    [
+     1461,
+     1540
+    ]
+   ],
+   "count": 79,
+   "note": "RB bit bus, 63 decoders, 10 digit gates"
+  },
+  "emit.head": {
+   "ranges": [
+    [
+     1540,
+     1981
+    ]
+   ],
+   "count": 441,
+   "note": "def <fn>(<arg>):\\n    _v0 = list(<arg>)\\n    _v1 = ; ok/reject start edges"
+  },
+  "emit.reject": {
+   "ranges": [
+    [
+     1981,
+     2014
+    ]
+   ],
+   "count": 33,
+   "note": "# UNSUPPORTED\\n EOS"
+  },
+  "emit.tail": {
+   "ranges": [
+    [
+     2014,
+     2050
+    ]
+   ],
+   "count": 36,
+   "note": "\\n    return _v<1|2>\\n EOS"
+  },
+  "emit.second_line": {
+   "ranges": [
+    [
+     2050,
+     2071
+    ]
+   ],
+   "count": 21,
+   "note": "\\n    _v2 =  (sets CUR2)"
+  },
+  "emit.template_trie": {
+   "ranges": [
+    [
+     2074,
+     2077
+    ],
+    [
+     2080,
+     2086
+    ],
+    [
+     2089,
+     2132
+    ],
+    [
+     2135,
+     2137
+    ],
+    [
+     2140,
+     2153
+    ],
+    [
+     2156,
+     2171
+    ],
+    [
+     2174,
+     2176
+    ],
+    [
+     2179,
+     2192
+    ],
+    [
+     2195,
+     2210
+    ],
+    [
+     2213,
+     2230
+    ],
+    [
+     2233,
+     2250
+    ],
+    [
+     2253,
+     2299
+    ],
+    [
+     2302,
+     2348
+    ],
+    [
+     2351,
+     2355
+    ],
+    [
+     2358,
+     2400
+    ],
+    [
+     2403,
+     2442
+    ],
+    [
+     2445,
+     2486
+    ],
+    [
+     2489,
+     2538
+    ],
+    [
+     2541,
+     2544
+    ],
+    [
+     2547,
+     2567
+    ],
+    [
+     2570,
+     2575
+    ],
+    [
+     2578,
+     2611
+    ],
+    [
+     2614,
+     2633
+    ],
+    [
+     2636,
+     2650
+    ],
+    [
+     2653,
+     2663
+    ],
+    [
+     2666,
+     2677
+    ],
+    [
+     2680,
+     2683
+    ],
+    [
+     2686,
+     2737
+    ],
+    [
+     2740,
+     2759
+    ],
+    [
+     2762,
+     2767
+    ],
+    [
+     2770,
+     2822
+    ],
+    [
+     2825,
+     2877
+    ]
+   ],
+   "count": 710,
+   "note": "shared expression trie (stage 003)"
+  },
+  "emit.family_groups": {
+   "ranges": [
+    [
+     2071,
+     2074
+    ],
+    [
+     2077,
+     2080
+    ],
+    [
+     2086,
+     2089
+    ],
+    [
+     2132,
+     2135
+    ],
+    [
+     2137,
+     2140
+    ],
+    [
+     2153,
+     2156
+    ],
+    [
+     2171,
+     2174
+    ],
+    [
+     2176,
+     2179
+    ],
+    [
+     2192,
+     2195
+    ],
+    [
+     2210,
+     2213
+    ],
+    [
+     2230,
+     2233
+    ],
+    [
+     2250,
+     2253
+    ],
+    [
+     2299,
+     2302
+    ],
+    [
+     2348,
+     2351
+    ],
+    [
+     2355,
+     2358
+    ],
+    [
+     2400,
+     2403
+    ],
+    [
+     2442,
+     2445
+    ],
+    [
+     2486,
+     2489
+    ],
+    [
+     2538,
+     2541
+    ],
+    [
+     2544,
+     2547
+    ],
+    [
+     2567,
+     2570
+    ],
+    [
+     2575,
+     2578
+    ],
+    [
+     2611,
+     2614
+    ],
+    [
+     2633,
+     2636
+    ],
+    [
+     2650,
+     2653
+    ],
+    [
+     2663,
+     2666
+    ],
+    [
+     2677,
+     2680
+    ],
+    [
+     2683,
+     2686
+    ],
+    [
+     2737,
+     2740
+    ],
+    [
+     2759,
+     2762
+    ],
+    [
+     2767,
+     2770
+    ],
+    [
+     2822,
+     2825
+    ]
+   ],
+   "count": 96,
+   "note": "OR of family flags for a trie branch (op-slot selected by CUR2)"
+  }
+ },
+ "notes": {
+  "language_trie_nodes": 436,
+  "expression_trie_nodes": 282,
+  "families_with_learned_windows": [
+   "filter>",
+   "filter>=",
+   "filter<",
+   "filter<=",
+   "filter==",
+   "filter!=",
+   "map_add",
+   "map_subtract",
+   "map_multiply",
+   "map_negate",
+   "map_abs",
+   "map_square",
+   "sort_asc",
+   "sort_desc",
+   "reverse",
+   "dedup",
+   "take",
+   "reduce_sum",
+   "reduce_count",
+   "reduce_min",
+   "reduce_max"
+  ],
+  "share_arg_reader": true,
+  "identifier_code": {
+   "A": 1,
+   "B": 2,
+   "C": 3,
+   "D": 4,
+   "E": 5,
+   "F": 6,
+   "G": 7,
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provenance/diag_ablation.json

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provenance/diag_counterfactual.json

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provenance/diag_empty_data.json

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provenance/diag_learning_curve.json

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provenance/diag_mechanism.json

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+   "base_ok": true,
+   "variant_ok": true,
+   "output_changed_as_label": true
+  },
+  {
+   "change": "names_moved",
+   "base_ok": true,
+   "variant_ok": true,
+   "output_changed_as_label": true
+  },
+  {
+   "change": "constant_changed",
+   "base_ok": true,
+   "variant_ok": true,
+   "output_changed_as_label": true
+  },
+  {
+   "change": "fn_renamed",
+   "base_ok": true,
+   "variant_ok": true,
+   "output_changed_as_label": true
+  },
+  {
+   "change": "arg_renamed",
+   "base_ok": true,
+   "variant_ok": true,
+   "output_changed_as_label": true
+  },
+  {
+   "change": "order_reversed",
+   "base_ok": true,
+   "variant_ok": true,
+   "output_changed_as_label": true
+  },
+  {
+   "change": "names_moved",
+   "base_ok": true,
+   "variant_ok": true,
+   "output_changed_as_label": true
+  },
+  {
+   "change": "fn_renamed",
+   "base_ok": true,
+   "variant_ok": true,
+   "output_changed_as_label": true
+  }
+ ],
+ "example": "Write a function named \"top\" with parameter \"xs\". Keep numbers at least 3, then sort them from largest to smallest.",
+ "example_output": "def top(xs):\n    _v0 = list(xs)\n    _v1 = [_x for _x in _v0 if _x >= 3]\n    _v2 = sorted(_v1, reverse=True)\n    return _v2\n",
+ "prefix_phase0_active_unit_counts_by_block": {
+  "en.lex": 65,
+  "parse.bit_detectors": 320,
+  "en.names": 250,
+  "en.trie": 75,
+  "parse.fn_buffer": 1163,
+  "parse.arg_buffer": 620,
+  "en.commit": 187,
+  "en.literal": 44,
+  "en.reject": 94,
+  "emit.select": 126,
+  "emit.head": 42,
+  "emit.family_groups": 420
+ }
+}

provenance/induced_grammar.json

@@ -0,0 +1,3743 @@
+{
+ "cues": [
+  {
+   "text": "be called \"",
+   "role": "fn",
+   "support": [
+    "teach-p0010",
+    "teach-p0016",
+    "teach-p0023",
+    "teach-p0029",
+    "teach-p0037",
+    "teach-p0040",
+    "teach-p0048",
+    "teach-p0053",
+    "teach-p0056",
+    "teach-p0058",
+    "teach-p0065",
+    "teach-p0069",
+    "teach-p0073",
+    "teach-p0074",
+    "teach-p0076",
+    "teach-p0078",
+    "teach-p0106",
+    "teach-p0116",
+    "teach-p0160",
+    "teach-p0164",
+    "teach-p0166",
+    "teach-p0190",
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+    "teach-p0200",
+    "teach-p0225",
+    "teach-p0228",
+    "teach-p0232",
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+    "teach-p0284",
+    "teach-p0287",
+    "teach-p0291",
+    "teach-p0294",
+    "teach-p0300",
+    "teach-p0301",
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+    "teach-p0340",
+    "teach-p0351",
+    "teach-p0354",
+    "teach-p0370",
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+    "teach-p0397",
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+    "teach-p0448",
+    "teach-p0460",
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+    "teach-p0700",
+    "teach-p0720",
+    "teach-p0722",
+    "teach-p0725",
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+    "teach-p0737",
+    "teach-p0738",
+    "teach-p0754",
+    "teach-p0760",
+    "teach-p0767",
+    "teach-p0777",
+    "teach-p0778",
+    "teach-p0781",
+    "teach-p0790",
+    "teach-p0791",
+    "teach-p0793",
+    "teach-p0794",
+    "teach-p0806",
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+    "teach-p0808",
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+    "teach-p0814",
+    "teach-p0833",
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+    "teach-p0851",
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+    "teach-p0867",
+    "teach-p0868",
+    "teach-p0871",
+    "teach-p0881",
+    "teach-p0882",
+    "teach-p0887",
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+    "teach-p0904",
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+    "teach-p0921",
+    "teach-p0928",
+    "teach-p0935",
+    "teach-p0950",
+    "teach-p0969",
+    "teach-p0974",
+    "teach-p0976",
+    "teach-p0990",
+    "teach-p0992",
+    "teach-p0995",
+    "teach-p1003",
+    "teach-p1015",
+    "teach-p1020"
+   ]
+  },
+  {
+   "text": "define \"",
+   "role": "fn",
+   "support": [
+    "teach-p0004",
+    "teach-p0007",
+    "teach-p0009",
+    "teach-p0012",
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+    "teach-p0067",
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+    "teach-p0093",
+    "teach-p0117",
+    "teach-p0123",
+    "teach-p0128",
+    "teach-p0139",
+    "teach-p0140",
+    "teach-p0142",
+    "teach-p0175",
+    "teach-p0176",
+    "teach-p0187",
+    "teach-p0195",
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+    "teach-p0203",
+    "teach-p0215",
+    "teach-p0220",
+    "teach-p0223",
+    "teach-p0224",
+    "teach-p0231",
+    "teach-p0239",
+    "teach-p0240",
+    "teach-p0242",
+    "teach-p0257",
+    "teach-p0277",
+    "teach-p0293",
+    "teach-p0298",
+    "teach-p0304",
+    "teach-p0305",
+    "teach-p0317",
+    "teach-p0327",
+    "teach-p0339",
+    "teach-p0353",
+    "teach-p0356",
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+    "teach-p0359",
+    "teach-p0373",
+    "teach-p0375",
+    "teach-p0376",
+    "teach-p0383",
+    "teach-p0386",
+    "teach-p0391",
+    "teach-p0392",
+    "teach-p0433",
+    "teach-p0442",
+    "teach-p0443",
+    "teach-p0477",
+    "teach-p0489",
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+    "teach-p0530",
+    "teach-p0546",
+    "teach-p0550",
+    "teach-p0551",
+    "teach-p0561",
+    "teach-p0567",
+    "teach-p0570",
+    "teach-p0574",
+    "teach-p0580",
+    "teach-p0581",
+    "teach-p0588",
+    "teach-p0591",
+    "teach-p0603",
+    "teach-p0610",
+    "teach-p0617",
+    "teach-p0625",
+    "teach-p0631",
+    "teach-p0636",
+    "teach-p0637",
+    "teach-p0641",
+    "teach-p0643",
+    "teach-p0653",
+    "teach-p0656",
+    "teach-p0661",
+    "teach-p0666",
+    "teach-p0674",
+    "teach-p0679",
+    "teach-p0680",
+    "teach-p0695",
+    "teach-p0711",
+    "teach-p0727",
+    "teach-p0732",
+    "teach-p0739",
+    "teach-p0741",
+    "teach-p0749",
+    "teach-p0783",
+    "teach-p0789",
+    "teach-p0812",
+    "teach-p0818",
+    "teach-p0839",
+    "teach-p0850",
+    "teach-p0852",
+    "teach-p0855",
+    "teach-p0861",
+    "teach-p0878",
+    "teach-p0885",
+    "teach-p0888",
+    "teach-p0891",
+    "teach-p0897",
+    "teach-p0912",
+    "teach-p0914",
+    "teach-p0918",
+    "teach-p0919",
+    "teach-p0930",
+    "teach-p0943",
+    "teach-p0951",
+    "teach-p0965",
+    "teach-p0968",
+    "teach-p0970",
+    "teach-p0975",
+    "teach-p0979",
+    "teach-p0984",
+    "teach-p0993",
+    "teach-p1009",
+    "teach-p1023"
+   ]
+  },
+  {
+   "text": "function \"",
+   "role": "fn",
+   "support": [
+    "teach-p0000",
+    "teach-p0003",
+    "teach-p0008",
+    "teach-p0015",
+    "teach-p0017",
+    "teach-p0018",
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+    "teach-p0054",
+    "teach-p0060",
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+    "teach-p0068",
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+    "teach-p0750",
+    "teach-p0752",
+    "teach-p0753",
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+    "teach-p1000",
+    "teach-p1016",
+    "teach-p1021",
+    "teach-p1022"
+   ]
+  },
+  {
+   "text": "function called \"",
+   "role": "fn",
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+    "teach-p0928",
+    "teach-p0931",
+    "teach-p0932",
+    "teach-p0933",
+    "teach-p0934",
+    "teach-p0935",
+    "teach-p0936",
+    "teach-p0937",
+    "teach-p0938",
+    "teach-p0939",
+    "teach-p0940",
+    "teach-p0944",
+    "teach-p0945",
+    "teach-p0946",
+    "teach-p0950",
+    "teach-p0957",
+    "teach-p0961",
+    "teach-p0966",
+    "teach-p0967",
+    "teach-p0969",
+    "teach-p0971",
+    "teach-p0973",
+    "teach-p0974",
+    "teach-p0976",
+    "teach-p0977",
+    "teach-p0978",
+    "teach-p0983",
+    "teach-p0985",
+    "teach-p0987",
+    "teach-p0989",
+    "teach-p0990",
+    "teach-p0992",
+    "teach-p0995",
+    "teach-p0996",
+    "teach-p0998",
+    "teach-p1000",
+    "teach-p1003",
+    "teach-p1004",
+    "teach-p1012",
+    "teach-p1015",
+    "teach-p1016",
+    "teach-p1017",
+    "teach-p1020",
+    "teach-p1022"
+   ]
+  },
+  {
+   "text": "list called \"",
+   "role": "arg",
+   "support": [
+    "teach-p0001",
+    "teach-p0002",
+    "teach-p0066",
+    "teach-p0081",
+    "teach-p0083",
+    "teach-p0086",
+    "teach-p0094",
+    "teach-p0104",
+    "teach-p0107",
+    "teach-p0110",
+    "teach-p0121",
+    "teach-p0133",
+    "teach-p0136",
+    "teach-p0143",
+    "teach-p0144",
+    "teach-p0157",
+    "teach-p0170",
+    "teach-p0172",
+    "teach-p0179",
+    "teach-p0184",
+    "teach-p0186",
+    "teach-p0196",
+    "teach-p0202",
+    "teach-p0216",
+    "teach-p0218",
+    "teach-p0230",
+    "teach-p0234",
+    "teach-p0243",
+    "teach-p0263",
+    "teach-p0264",
+    "teach-p0270",
+    "teach-p0278",
+    "teach-p0285",
+    "teach-p0315",
+    "teach-p0319",
+    "teach-p0323",
+    "teach-p0331",
+    "teach-p0341",
+    "teach-p0348",
+    "teach-p0371",
+    "teach-p0374",
+    "teach-p0378",
+    "teach-p0380",
+    "teach-p0381",
+    "teach-p0396",
+    "teach-p0399",
+    "teach-p0404",
+    "teach-p0416",
+    "teach-p0422",
+    "teach-p0440",
+    "teach-p0450",
+    "teach-p0451",
+    "teach-p0455",
+    "teach-p0463",
+    "teach-p0487",
+    "teach-p0488",
+    "teach-p0496",
+    "teach-p0503",
+    "teach-p0504",
+    "teach-p0506",
+    "teach-p0517",
+    "teach-p0520",
+    "teach-p0521",
+    "teach-p0526",
+    "teach-p0527",
+    "teach-p0541",
+    "teach-p0544",
+    "teach-p0562",
+    "teach-p0590",
+    "teach-p0599",
+    "teach-p0600",
+    "teach-p0605",
+    "teach-p0614",
+    "teach-p0618",
+    "teach-p0621",
+    "teach-p0633",
+    "teach-p0640",
+    "teach-p0663",
+    "teach-p0672",
+    "teach-p0683",
+    "teach-p0696",
+    "teach-p0698",
+    "teach-p0707",
+    "teach-p0710",
+    "teach-p0718",
+    "teach-p0723",
+    "teach-p0724",
+    "teach-p0736",
+    "teach-p0746",
+    "teach-p0751",
+    "teach-p0755",
+    "teach-p0759",
+    "teach-p0786",
+    "teach-p0795",
+    "teach-p0797",
+    "teach-p0800",
+    "teach-p0809",
+    "teach-p0821",
+    "teach-p0826",
+    "teach-p0834",
+    "teach-p0840",
+    "teach-p0854",
+    "teach-p0856",
+    "teach-p0874",
+    "teach-p0883",
+    "teach-p0884",
+    "teach-p0893",
+    "teach-p0909",
+    "teach-p0911",
+    "teach-p0920",
+    "teach-p0922",
+    "teach-p0926",
+    "teach-p0929",
+    "teach-p0941",
+    "teach-p0942",
+    "teach-p0948",
+    "teach-p0952",
+    "teach-p0953",
+    "teach-p0955",
+    "teach-p0958",
+    "teach-p0972",
+    "teach-p0982",
+    "teach-p0986",
+    "teach-p0988",
+    "teach-p0994",
+    "teach-p0999",
+    "teach-p1002",
+    "teach-p1005",
+    "teach-p1007",
+    "teach-p1008",
+    "teach-p1010",
+    "teach-p1014"
+   ]
+  },
+  {
+   "text": "named \"",
+   "role": "fn",
+   "support": [
+    "teach-p0001",
+    "teach-p0002",
+    "teach-p0006",
+    "teach-p0011",
+    "teach-p0013",
+    "teach-p0019",
+    "teach-p0020",
+    "teach-p0021",
+    "teach-p0024",
+    "teach-p0027",
+    "teach-p0034",
+    "teach-p0039",
+    "teach-p0043",
+    "teach-p0047",
+    "teach-p0052",
+    "teach-p0055",
+    "teach-p0057",
+    "teach-p0062",
+    "teach-p0063",
+    "teach-p0066",
+    "teach-p0071",
+    "teach-p0079",
+    "teach-p0081",
+    "teach-p0083",
+    "teach-p0086",
+    "teach-p0089",
+    "teach-p0094",
+    "teach-p0097",
+    "teach-p0099",
+    "teach-p0100",
+    "teach-p0101",
+    "teach-p0103",
+    "teach-p0104",
+    "teach-p0107",
+    "teach-p0110",
+    "teach-p0112",
+    "teach-p0113",
+    "teach-p0114",
+    "teach-p0120",
+    "teach-p0121",
+    "teach-p0131",
+    "teach-p0133",
+    "teach-p0134",
+    "teach-p0136",
+    "teach-p0137",
+    "teach-p0143",
+    "teach-p0144",
+    "teach-p0146",
+    "teach-p0151",
+    "teach-p0152",
+    "teach-p0155",
+    "teach-p0157",
+    "teach-p0158",
+    "teach-p0161",
+    "teach-p0162",
+    "teach-p0165",
+    "teach-p0170",
+    "teach-p0172",
+    "teach-p0173",
+    "teach-p0174",
+    "teach-p0179",
+    "teach-p0180",
+    "teach-p0181",
+    "teach-p0183",
+    "teach-p0184",
+    "teach-p0185",
+    "teach-p0186",
+    "teach-p0189",
+    "teach-p0194",
+    "teach-p0196",
+    "teach-p0198",
+    "teach-p0202",
+    "teach-p0206",
+    "teach-p0210",
+    "teach-p0214",
+    "teach-p0216",
+    "teach-p0218",
+    "teach-p0222",
+    "teach-p0226",
+    "teach-p0227",
+    "teach-p0229",
+    "teach-p0230",
+    "teach-p0234",
+    "teach-p0243",
+    "teach-p0256",
+    "teach-p0259",
+    "teach-p0260",
+    "teach-p0261",
+    "teach-p0263",
+    "teach-p0264",
+    "teach-p0266",
+    "teach-p0269",
+    "teach-p0270",
+    "teach-p0271",
+    "teach-p0273",
+    "teach-p0278",
+    "teach-p0280",
+    "teach-p0281",
+    "teach-p0285",
+    "teach-p0292",
+    "teach-p0299",
+    "teach-p0312",
+    "teach-p0315",
+    "teach-p0319",
+    "teach-p0321",
+    "teach-p0323",
+    "teach-p0331",
+    "teach-p0334",
+    "teach-p0338",
+    "teach-p0341",
+    "teach-p0343",
+    "teach-p0348",
+    "teach-p0352",
+    "teach-p0363",
+    "teach-p0365",
+    "teach-p0371",
+    "teach-p0374",
+    "teach-p0378",
+    "teach-p0380",
+    "teach-p0381",
+    "teach-p0384",
+    "teach-p0387",
+    "teach-p0396",
+    "teach-p0399",
+    "teach-p0404",
+    "teach-p0405",
+    "teach-p0413",
+    "teach-p0416",
+    "teach-p0422",
+    "teach-p0423",
+    "teach-p0426",
+    "teach-p0430",
+    "teach-p0440",
+    "teach-p0441",
+    "teach-p0446",
+    "teach-p0449",
+    "teach-p0450",
+    "teach-p0451",
+    "teach-p0455",
+    "teach-p0456",
+    "teach-p0457",
+    "teach-p0463",
+    "teach-p0466",
+    "teach-p0467",
+    "teach-p0476",
+    "teach-p0478",
+    "teach-p0483",
+    "teach-p0487",
+    "teach-p0488",
+    "teach-p0494",
+    "teach-p0496",
+    "teach-p0500",
+    "teach-p0503",
+    "teach-p0504",
+    "teach-p0505",
+    "teach-p0506",
+    "teach-p0511",
+    "teach-p0515",
+    "teach-p0517",
+    "teach-p0520",
+    "teach-p0521",
+    "teach-p0525",
+    "teach-p0526",
+    "teach-p0527",
+    "teach-p0532",
+    "teach-p0535",
+    "teach-p0541",
+    "teach-p0544",
+    "teach-p0547",
+    "teach-p0548",
+    "teach-p0552",
+    "teach-p0556",
+    "teach-p0558",
+    "teach-p0562",
+    "teach-p0577",
+    "teach-p0579",
+    "teach-p0587",
+    "teach-p0590",
+    "teach-p0592",
+    "teach-p0599",
+    "teach-p0600",
+    "teach-p0605",
+    "teach-p0608",
+    "teach-p0613",
+    "teach-p0614",
+    "teach-p0618",
+    "teach-p0621",
+    "teach-p0628",
+    "teach-p0629",
+    "teach-p0630",
+    "teach-p0633",
+    "teach-p0634",
+    "teach-p0640",
+    "teach-p0648",
+    "teach-p0659",
+    "teach-p0660",
+    "teach-p0663",
+    "teach-p0667",
+    "teach-p0670",
+    "teach-p0672",
+    "teach-p0673",
+    "teach-p0683",
+    "teach-p0686",
+    "teach-p0696",
+    "teach-p0698",
+    "teach-p0699",
+    "teach-p0705",
+    "teach-p0707",
+    "teach-p0708",
+    "teach-p0710",
+    "teach-p0712",
+    "teach-p0717",
+    "teach-p0718",
+    "teach-p0721",
+    "teach-p0723",
+    "teach-p0724",
+    "teach-p0731",
+    "teach-p0733",
+    "teach-p0736",
+    "teach-p0745",
+    "teach-p0746",
+    "teach-p0751",
+    "teach-p0755",
+    "teach-p0757",
+    "teach-p0759",
+    "teach-p0761",
+    "teach-p0772",
+    "teach-p0775",
+    "teach-p0784",
+    "teach-p0785",
+    "teach-p0786",
+    "teach-p0787",
+    "teach-p0792",
+    "teach-p0795",
+    "teach-p0797",
+    "teach-p0800",
+    "teach-p0804",
+    "teach-p0805",
+    "teach-p0809",
+    "teach-p0810",
+    "teach-p0817",
+    "teach-p0821",
+    "teach-p0826",
+    "teach-p0828",
+    "teach-p0834",
+    "teach-p0837",
+    "teach-p0840",
+    "teach-p0841",
+    "teach-p0844",
+    "teach-p0854",
+    "teach-p0856",
+    "teach-p0857",
+    "teach-p0863",
+    "teach-p0865",
+    "teach-p0870",
+    "teach-p0874",
+    "teach-p0876",
+    "teach-p0883",
+    "teach-p0884",
+    "teach-p0886",
+    "teach-p0890",
+    "teach-p0893",
+    "teach-p0895",
+    "teach-p0898",
+    "teach-p0909",
+    "teach-p0910",
+    "teach-p0911",
+    "teach-p0915",
+    "teach-p0917",
+    "teach-p0920",
+    "teach-p0922",
+    "teach-p0926",
+    "teach-p0929",
+    "teach-p0941",
+    "teach-p0942",
+    "teach-p0947",
+    "teach-p0948",
+    "teach-p0949",
+    "teach-p0952",
+    "teach-p0953",
+    "teach-p0954",
+    "teach-p0955",
+    "teach-p0956",
+    "teach-p0958",
+    "teach-p0960",
+    "teach-p0962",
+    "teach-p0963",
+    "teach-p0972",
+    "teach-p0980",
+    "teach-p0982",
+    "teach-p0986",
+    "teach-p0988",
+    "teach-p0994",
+    "teach-p0999",
+    "teach-p1001",
+    "teach-p1002",
+    "teach-p1005",
+    "teach-p1006",
+    "teach-p1007",
+    "teach-p1008",
+    "teach-p1010",
+    "teach-p1011",
+    "teach-p1013",
+    "teach-p1014",
+    "teach-p1018",
+    "teach-p1019"
+   ]
+  },
+  {
+   "text": "parameter \"",
+   "role": "arg",
+   "support": [
+    "teach-p0006",
+    "teach-p0008",
+    "teach-p0011",
+    "teach-p0013",
+    "teach-p0015",
+    "teach-p0017",
+    "teach-p0018",
+    "teach-p0019",
+    "teach-p0020",
+    "teach-p0021",
+    "teach-p0024",
+    "teach-p0027",
+    "teach-p0030",
+    "teach-p0034",
+    "teach-p0039",
+    "teach-p0043",
+    "teach-p0047",
+    "teach-p0052",
+    "teach-p0055",
+    "teach-p0057",
+    "teach-p0062",
+    "teach-p0063",
+    "teach-p0064",
+    "teach-p0068",
+    "teach-p0071",
+    "teach-p0075",
+    "teach-p0077",
+    "teach-p0079",
+    "teach-p0089",
+    "teach-p0096",
+    "teach-p0097",
+    "teach-p0098",
+    "teach-p0099",
+    "teach-p0100",
+    "teach-p0101",
+    "teach-p0103",
+    "teach-p0105",
+    "teach-p0108",
+    "teach-p0111",
+    "teach-p0112",
+    "teach-p0113",
+    "teach-p0114",
+    "teach-p0115",
+    "teach-p0120",
+    "teach-p0125",
+    "teach-p0131",
+    "teach-p0134",
+    "teach-p0135",
+    "teach-p0137",
+    "teach-p0138",
+    "teach-p0145",
+    "teach-p0146",
+    "teach-p0148",
+    "teach-p0151",
+    "teach-p0152",
+    "teach-p0155",
+    "teach-p0158",
+    "teach-p0161",
+    "teach-p0162",
+    "teach-p0165",
+    "teach-p0173",
+    "teach-p0174",
+    "teach-p0180",
+    "teach-p0181",
+    "teach-p0183",
+    "teach-p0185",
+    "teach-p0189",
+    "teach-p0192",
+    "teach-p0194",
+    "teach-p0198",
+    "teach-p0206",
+    "teach-p0207",
+    "teach-p0210",
+    "teach-p0214",
+    "teach-p0219",
+    "teach-p0222",
+    "teach-p0226",
+    "teach-p0227",
+    "teach-p0229",
+    "teach-p0233",
+    "teach-p0235",
+    "teach-p0244",
+    "teach-p0251",
+    "teach-p0256",
+    "teach-p0258",
+    "teach-p0259",
+    "teach-p0260",
+    "teach-p0261",
+    "teach-p0266",
+    "teach-p0269",
+    "teach-p0271",
+    "teach-p0273",
+    "teach-p0279",
+    "teach-p0280",
+    "teach-p0281",
+    "teach-p0288",
+    "teach-p0292",
+    "teach-p0299",
+    "teach-p0302",
+    "teach-p0306",
+    "teach-p0308",
+    "teach-p0312",
+    "teach-p0316",
+    "teach-p0318",
+    "teach-p0321",
+    "teach-p0325",
+    "teach-p0334",
+    "teach-p0338",
+    "teach-p0343",
+    "teach-p0344",
+    "teach-p0345",
+    "teach-p0347",
+    "teach-p0352",
+    "teach-p0363",
+    "teach-p0365",
+    "teach-p0366",
+    "teach-p0367",
+    "teach-p0377",
+    "teach-p0382",
+    "teach-p0384",
+    "teach-p0387",
+    "teach-p0388",
+    "teach-p0393",
+    "teach-p0395",
+    "teach-p0405",
+    "teach-p0408",
+    "teach-p0410",
+    "teach-p0413",
+    "teach-p0415",
+    "teach-p0420",
+    "teach-p0423",
+    "teach-p0424",
+    "teach-p0426",
+    "teach-p0429",
+    "teach-p0430",
+    "teach-p0441",
+    "teach-p0445",
+    "teach-p0446",
+    "teach-p0447",
+    "teach-p0449",
+    "teach-p0454",
+    "teach-p0456",
+    "teach-p0457",
+    "teach-p0466",
+    "teach-p0467",
+    "teach-p0476",
+    "teach-p0478",
+    "teach-p0479",
+    "teach-p0483",
+    "teach-p0485",
+    "teach-p0486",
+    "teach-p0492",
+    "teach-p0494",
+    "teach-p0497",
+    "teach-p0498",
+    "teach-p0500",
+    "teach-p0505",
+    "teach-p0510",
+    "teach-p0511",
+    "teach-p0513",
+    "teach-p0515",
+    "teach-p0519",
+    "teach-p0522",
+    "teach-p0524",
+    "teach-p0525",
+    "teach-p0532",
+    "teach-p0533",
+    "teach-p0535",
+    "teach-p0547",
+    "teach-p0548",
+    "teach-p0552",
+    "teach-p0553",
+    "teach-p0556",
+    "teach-p0557",
+    "teach-p0558",
+    "teach-p0560",
+    "teach-p0563",
+    "teach-p0577",
+    "teach-p0579",
+    "teach-p0587",
+    "teach-p0592",
+    "teach-p0595",
+    "teach-p0596",
+    "teach-p0601",
+    "teach-p0608",
+    "teach-p0613",
+    "teach-p0615",
+    "teach-p0616",
+    "teach-p0624",
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+    "teach-p0807",
+    "teach-p0809",
+    "teach-p0810",
+    "teach-p0811",
+    "teach-p0812",
+    "teach-p0814",
+    "teach-p0815",
+    "teach-p0817",
+    "teach-p0818",
+    "teach-p0819",
+    "teach-p0821",
+    "teach-p0822",
+    "teach-p0823",
+    "teach-p0824",
+    "teach-p0825",
+    "teach-p0826",
+    "teach-p0827",
+    "teach-p0828",
+    "teach-p0829",
+    "teach-p0830",
+    "teach-p0831",
+    "teach-p0832",
+    "teach-p0833",
+    "teach-p0834",
+    "teach-p0835",
+    "teach-p0836",
+    "teach-p0838",
+    "teach-p0839",
+    "teach-p0841",
+    "teach-p0843",
+    "teach-p0844",
+    "teach-p0845",
+    "teach-p0846",
+    "teach-p0848",
+    "teach-p0849",
+    "teach-p0850",
+    "teach-p0851",
+    "teach-p0852",
+    "teach-p0855",
+    "teach-p0856",
+    "teach-p0857",
+    "teach-p0859",
+    "teach-p0861",
+    "teach-p0862",
+    "teach-p0863",
+    "teach-p0866",
+    "teach-p0867",
+    "teach-p0868",
+    "teach-p0869",
+    "teach-p0870",
+    "teach-p0871",
+    "teach-p0873",
+    "teach-p0874",
+    "teach-p0875",
+    "teach-p0876",
+    "teach-p0877",
+    "teach-p0878",
+    "teach-p0879",
+    "teach-p0880",
+    "teach-p0881",
+    "teach-p0883",
+    "teach-p0885",
+    "teach-p0887",
+    "teach-p0888",
+    "teach-p0890",
+    "teach-p0891",
+    "teach-p0893",
+    "teach-p0894",
+    "teach-p0897",
+    "teach-p0899",
+    "teach-p0900",
+    "teach-p0901",
+    "teach-p0903",
+    "teach-p0904",
+    "teach-p0905",
+    "teach-p0906",
+    "teach-p0908",
+    "teach-p0909",
+    "teach-p0911",
+    "teach-p0912",
+    "teach-p0913",
+    "teach-p0914",
+    "teach-p0915",
+    "teach-p0916",
+    "teach-p0917",
+    "teach-p0918",
+    "teach-p0919",
+    "teach-p0920",
+    "teach-p0922",
+    "teach-p0923",
+    "teach-p0926",
+    "teach-p0927",
+    "teach-p0929",
+    "teach-p0930",
+    "teach-p0932",
+    "teach-p0933",
+    "teach-p0934",
+    "teach-p0935",
+    "teach-p0937",
+    "teach-p0938",
+    "teach-p0939",
+    "teach-p0940",
+    "teach-p0943",
+    "teach-p0945",
+    "teach-p0947",
+    "teach-p0948",
+    "teach-p0951",
+    "teach-p0952",
+    "teach-p0953",
+    "teach-p0954",
+    "teach-p0955",
+    "teach-p0956",
+    "teach-p0957",
+    "teach-p0958",
+    "teach-p0959",
+    "teach-p0960",
+    "teach-p0963",
+    "teach-p0964",
+    "teach-p0965",
+    "teach-p0966",
+    "teach-p0968",
+    "teach-p0969",
+    "teach-p0970",
+    "teach-p0972",
+    "teach-p0974",
+    "teach-p0975",
+    "teach-p0976",
+    "teach-p0977",
+    "teach-p0979",
+    "teach-p0980",
+    "teach-p0981",
+    "teach-p0982",
+    "teach-p0983",
+    "teach-p0984",
+    "teach-p0987",
+    "teach-p0988",
+    "teach-p0989",
+    "teach-p0991",
+    "teach-p0992",
+    "teach-p0993",
+    "teach-p0995",
+    "teach-p0996",
+    "teach-p0997",
+    "teach-p0998",
+    "teach-p0999",
+    "teach-p1000",
+    "teach-p1001",
+    "teach-p1002",
+    "teach-p1005",
+    "teach-p1006",
+    "teach-p1009",
+    "teach-p1010",
+    "teach-p1014",
+    "teach-p1015",
+    "teach-p1017",
+    "teach-p1020",
+    "teach-p1021",
+    "teach-p1023"
+   ]
+  }
+ ],
+ "reject_cues": [
+  {
+   "text": "characters",
+   "support": [
+    "teach-r027",
+    "teach-r059"
+   ]
+  },
+  {
+   "text": "for",
+   "support": [
+    "teach-r003",
+    "teach-r011",
+    "teach-r035"
+   ]
+  },
+  {
+   "text": "integers",
+   "support": [
+    "teach-r019",
+    "teach-r043",
+    "teach-r051"
+   ]
+  }
+ ],
+ "validation_on_teaching": {
+  "positive_exact_intent": 1024,
+  "positive_n": 1024,
+  "reject_correct": 64,
+  "reject_n": 64,
+  "failures": []
+ },
+ "counts": {
+  "cues": 9,
+  "windows": 56,
+  "connectors": 2,
+  "reject_cues": 3
+ },
+ "refinement_log": [
+  "refine: dropping reverse window 'put''': its matches are covered by another window"
+ ],
+ "representation_sha256": "58af8e31cdd8cf163f4569c4ad35f12484888b8125387d5943a34242cebd6a28"
+}

runtime.py

@@ -0,0 +1,233 @@
+"""Fixed generic neural runtime: recurrent signed-add threshold network (task-neutral).
+
+Imports only numpy/json/hashlib. It never imports the task contract, interpreter, renderer, datasets or any
+expert/constructor code. Architecture id: rsat-v1.
+
+Symbols: bytes 0..255, BOS=256, EOS=257, SEP=258, PAD=259 (V = 260).
+Per-tick input x (270 channels): one-hot symbol (0..259), mode (260 = prefix, 261 = output), one-hot clock
+phase (262..269). Every external symbol occupies 8 ticks (phase 0..7) with its symbol and mode held.
+
+State: H bits, reset to 0 for every request. Synchronous update:
+    a_i = sum_{j: R[i,j]=+1} s_j - sum_{j: R[i,j]=-1} s_j + sum_{k: I[i,k]=+1} x_k - sum_{k: I[i,k]=-1} x_k
+    s'_i = 1 if a_i >= theta_i else 0
+Output (after the 8th tick of every OUTPUT-mode symbol):
+    score_o = sum_{i: O[o,i]=+1} s_i - sum_{i: O[o,i]=-1} s_i + bias_o ;  emit smallest o with maximal score.
+Protocol: feed BOS then the request bytes in PREFIX mode; then feed SEP in OUTPUT mode (ending the prefix and
+starting generation); after each output-mode symbol emit one symbol and feed it back (OUTPUT mode).
+EOS ends generation. Emitting BOS/SEP/PAD, or more than 2,048 source bytes, is a failure.
+
+Integer bounds (proved, enforced by validate()): connections in {-1,0,+1}; |a_i| <= H + 3 (one symbol, one
+mode, one phase channel active) <= 2,883 for H = 2,880; |score| <= H + 32,767 < 2^31. All accumulation is in
+int32; thresholds and biases are int16. No multiplication, matrix product, BLAS, einsum or attention is used:
+contributions are added/subtracted column by column.
+"""
+from __future__ import annotations
+
+import hashlib
+import json
+
+import numpy as np
+
+V, BOS, EOS, SEP, PAD = 260, 256, 257, 258, 259
+MODE_PREFIX, MODE_OUTPUT = 260, 261
+PHASE0 = 262
+D_IN = 270
+TICKS = 8
+MAX_OUT_BYTES = 2048
+ARCH_ID = "rsat-v1"
+KEYS = ("R", "I", "O", "theta", "bias")
+
+
+def shapes(H):
+    return {"R": (H, H), "I": (H, D_IN), "O": (V, H), "theta": (H,), "bias": (V,)}
+
+
+def n_slots(H):
+    return H * H + 531 * H + 260
+
+
+def validate(arrs, H):
+    sh = shapes(H)
+    out = {}
+    for k in KEYS:
+        a = np.asarray(arrs[k])
+        if a.shape != sh[k]:
+            raise ValueError(f"{k}: shape {a.shape} != {sh[k]}")
+        if not np.issubdtype(a.dtype, np.integer):
+            raise ValueError(f"{k}: integer dtype required, got {a.dtype}")
+        if k in ("R", "I", "O"):
+            if a.size and (a.min() < -1 or a.max() > 1):
+                raise ValueError(f"{k}: connections must be -1, 0 or +1")
+            out[k] = a.astype(np.int8)
+        else:
+            if a.size and (a.min() < -32768 or a.max() > 32767):
+                raise ValueError(f"{k}: must fit signed 16-bit")
+            out[k] = a.astype(np.int16)
+    return out
+
+
+def weights_sha256(arrs):
+    h = hashlib.sha256()
+    for k in KEYS:
+        a = np.ascontiguousarray(arrs[k])
+        h.update(k.encode() + str(a.dtype).encode() + str(a.shape).encode() + a.tobytes())
+    return h.hexdigest()
+
+
+def save(path, arrs, config: dict):
+    meta = dict(config, architecture_id=ARCH_ID, weights_sha256=weights_sha256(arrs))
+    blob = np.frombuffer(json.dumps(meta, sort_keys=True).encode(), dtype=np.uint8)
+    np.savez_compressed(path, __meta__=blob, **{k: arrs[k] for k in KEYS})
+    return meta
+
+
+def load(path):
+    with np.load(path, allow_pickle=False) as z:
+        meta = json.loads(bytes(z["__meta__"]).decode())
+        arrs = {k: z[k].copy() for k in KEYS}
+    arrs = validate(arrs, int(meta["H"]))
+    if weights_sha256(arrs) != meta["weights_sha256"]:
+        raise ValueError("weights hash mismatch")
+    return arrs, meta
+
+
+class Net:
+    """Optimized CPU implementation (exactly equal to `reference_step`; see verify_runtime)."""
+
+    def __init__(self, arrs, H):
+        a = validate(arrs, H)
+        self.H = H
+        self.RT = np.ascontiguousarray(a["R"].T)        # row j = outgoing connections of source unit j
+        self.IT = np.ascontiguousarray(a["I"].T)        # row k = connections of input channel k
+        self.OT = np.ascontiguousarray(a["O"].T)        # row i = output connections of unit i
+        self.theta = a["theta"].astype(np.int32)
+        self.bias = a["bias"].astype(np.int32)
+        self.reset()
+
+    def reset(self):
+        self.s = np.zeros(self.H, dtype=bool)
+        self.rec = np.zeros(self.H, dtype=np.int32)    # sum_j R[:, j] s_j, maintained incrementally
+        self.ticks = 0
+
+    def step(self, sym, mode, phase):
+        a = self.rec + self.IT[sym] + self.IT[mode] + self.IT[PHASE0 + phase]   # int32 + int8 adds
+        new = a >= self.theta
+        on = np.flatnonzero(new & ~self.s)
+        off = np.flatnonzero(self.s & ~new)
+        if on.size:
+            self.rec += self.RT[on].sum(axis=0, dtype=np.int32)
+        if off.size:
+            self.rec -= self.RT[off].sum(axis=0, dtype=np.int32)
+        self.s = new
+        self.ticks += 1
+
+    def feed(self, sym, mode):
+        for p in range(TICKS):
+            self.step(sym, mode, p)
+
+    def scores(self):
+        act = np.flatnonzero(self.s)
+        sc = self.bias.copy()
+        if act.size:
+            sc += self.OT[act].sum(axis=0, dtype=np.int32)
+        return sc
+
+    def emit(self):
+        return int(np.argmax(self.scores()))   # argmax returns the smallest index among maxima
+
+
+def generate(net: Net, request: bytes, max_bytes=MAX_OUT_BYTES, detect_cycles=True):
+    """Returns dict(status, source_bytes, ticks). status: ok | invalid_symbol | too_long.
+    Exact cycle detection: generation is a deterministic function of (state before feeding, fed symbol);
+    if that pair repeats, the emitted sequence is periodic forever without EOS, so the outcome (too_long)
+    is decided early. The result equals running to the byte limit."""
+    net.reset()
+    net.feed(BOS, MODE_PREFIX)
+    for b in request:
+        net.feed(b, MODE_PREFIX)
+    cur = SEP
+    out = bytearray()
+    seen = set()
+    while True:
+        if detect_cycles:
+            key = (cur, np.packbits(net.s).tobytes())
+            if key in seen:
+                return {"status": "too_long", "cycle_detected": True, "source": bytes(out[:max_bytes]), "ticks": net.ticks}
+            seen.add(key)
+        net.feed(cur, MODE_OUTPUT)
+        y = net.emit()
+        if y == EOS:
+            return {"status": "ok", "source": bytes(out), "ticks": net.ticks}
+        if y >= 256:
+            return {"status": "invalid_symbol", "symbol": int(y), "source": bytes(out), "ticks": net.ticks}
+        out.append(y)
+        if len(out) > max_bytes:
+            return {"status": "too_long", "source": bytes(out[:max_bytes]), "ticks": net.ticks}
+        cur = y
+
+
+# ---------------- slow reference (definitional; small networks / short sequences) ----------------
+def reference_step(R, I, theta, s, x):
+    H = len(s)
+    new = [0] * H
+    for i in range(H):
+        acc = 0
+        for j in range(H):
+            if R[i][j] == 1 and s[j]:
+                acc += 1
+            elif R[i][j] == -1 and s[j]:
+                acc -= 1
+        for k in range(D_IN):
+            if I[i][k] == 1 and x[k]:
+                acc += 1
+            elif I[i][k] == -1 and x[k]:
+                acc -= 1
+        new[i] = 1 if acc >= theta[i] else 0
+    return new
+
+
+def reference_scores(O, bias, s):
+    out = []
+    for o in range(V):
+        acc = int(bias[o])
+        for i in range(len(s)):
+            if O[o][i] == 1 and s[i]:
+                acc += 1
+            elif O[o][i] == -1 and s[i]:
+                acc -= 1
+        out.append(acc)
+    return out
+
+
+def reference_generate(arrs, H, request: bytes, max_bytes=MAX_OUT_BYTES):
+    R, I, O = arrs["R"].tolist(), arrs["I"].tolist(), arrs["O"].tolist()
+    theta, bias = arrs["theta"].tolist(), arrs["bias"].tolist()
+    s = [0] * H
+    ticks = 0
+
+    def feed(sym, mode, s):
+        nonlocal ticks
+        for p in range(TICKS):
+            x = [0] * D_IN
+            x[sym] = 1
+            x[mode] = 1
+            x[PHASE0 + p] = 1
+            s = reference_step(R, I, theta, s, x)
+            ticks += 1
+        return s
+    s = feed(BOS, MODE_PREFIX, s)
+    for b in request:
+        s = feed(b, MODE_PREFIX, s)
+    cur, out = SEP, bytearray()
+    while True:
+        s = feed(cur, MODE_OUTPUT, s)
+        sc = reference_scores(O, bias, s)
+        y = max(range(V), key=lambda o: (sc[o], -o))
+        if y == EOS:
+            return {"status": "ok", "source": bytes(out), "ticks": ticks}
+        if y >= 256:
+            return {"status": "invalid_symbol", "symbol": y, "source": bytes(out), "ticks": ticks}
+        out.append(y)
+        if len(out) > max_bytes:
+            return {"status": "too_long", "source": bytes(out[:max_bytes]), "ticks": ticks}
+        cur = y

sched.py

@@ -0,0 +1,120 @@
+"""Mechanism-study scheduler (sched-v1) on the UNCHANGED pilot runtime (wspp.runtime.Net, rsat-v1).
+
+Protocol (identical to the pilot): reset state to zero; feed BOS then the raw payload bytes in PREFIX mode
+(8 ticks each, clock phase 0..7); feed SEP in OUTPUT mode; after the 8th tick of each output-mode symbol
+emit argmax (smallest id on ties) and feed it back in OUTPUT mode. A run ends at EOS, at an invalid special
+symbol (BOS/SEP/PAD), or when `max_symbols` symbols (EOS included) have been emitted without EOS.
+
+Timing vocabulary: tick = one synchronous state update; symbol cycle = 8 ticks (one external symbol);
+prefix = BOS + payload ticks; output = ticks spent feeding SEP and fed-back symbols; generation = both.
+
+Cycle fast-forward (exact): the future of a run is fully determined, at each output-symbol boundary
+(phase 0, OUTPUT mode, prefix fully consumed, no other scheduler buffer), by (recurrent state bits,
+incremental accumulator, symbol about to be fed). These are stored as exact byte strings in a dict keyed by
+the full tuple, so a hit implies exact equality (Python compares keys after hashing). On a hit the
+intervening emissions repeat forever; they are replayed literally until EOS-free cap exhaustion, so the
+emitted sequence equals literal execution up to the cap.
+"""
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+import numpy as np
+
+try:  # inside a fresh sandbox process only runtime.py + sched.py are present
+    import runtime as RT  # noqa: E402
+except ImportError:
+    ROOT = Path(__file__).resolve().parents[2]
+    sys.path.insert(0, str(ROOT))
+    from wspp import runtime as RT  # noqa: E402
+
+SCHED_VERSION = "sched-v1"
+
+
+def _boundary_key(net, cur):
+    return (int(cur), np.packbits(net.s).tobytes(), net.rec.tobytes())
+
+
+def run(net: RT.Net, payload: bytes, max_symbols: int, detect_cycles=True, trace=False, trace_units=12):
+    net.reset()
+    tr = [] if trace else None
+
+    def feed(sym, mode):
+        for p in range(RT.TICKS):
+            net.step(sym, mode, p)
+            if trace:
+                act = np.flatnonzero(net.s)
+                tr.append({"sym": int(sym), "mode": "prefix" if mode == RT.MODE_PREFIX else "output", "phase": p,
+                           "n_active": int(act.size), "active": act[:trace_units].tolist()})
+    feed(RT.BOS, RT.MODE_PREFIX)
+    for b in payload:
+        feed(b, RT.MODE_PREFIX)
+    prefix_ticks = net.ticks
+    cur = RT.SEP
+    out = []
+    seen = {}
+    fast_forwarded = False
+    while len(out) < max_symbols:
+        if detect_cycles:
+            k = _boundary_key(net, cur)
+            if k in seen:
+                j = seen[k]
+                period = out[j:]  # emissions between the two identical boundaries (all plain bytes, no EOS)
+                i = 0
+                while len(out) < max_symbols:
+                    out.append(period[i % len(period)])
+                    i += 1
+                fast_forwarded = True
+                break
+            seen[k] = len(out)
+        feed(cur, RT.MODE_OUTPUT)
+        sc = net.scores()
+        y = int(np.argmax(sc))
+        if trace:
+            top = np.argsort(-sc, kind="stable")[:3]
+            tr.append({"emit": y, "top_scores": [[int(t), int(sc[t])] for t in top]})
+        out.append(y)
+        if y == RT.EOS:
+            return _res("eos", out, prefix_ticks, net.ticks, fast_forwarded, tr)
+        if y >= 256:
+            return _res("invalid_symbol", out, prefix_ticks, net.ticks, fast_forwarded, tr)
+        cur = y
+    return _res("no_eos_within_cap", out, prefix_ticks, net.ticks, fast_forwarded, tr)
+
+
+def _res(status, out, prefix_ticks, ticks, ff, tr):
+    r = {"status": status, "symbols": out, "prefix_ticks": prefix_ticks, "output_ticks": ticks - prefix_ticks,
+         "fast_forwarded": ff}
+    if tr is not None:
+        r["trace"] = tr
+    return r
+
+
+def reference_run(arrs, H, payload: bytes, max_symbols: int):
+    """Definitional slow path (pure-Python reference_step / reference_scores), small networks only."""
+    R, I, O = arrs["R"].tolist(), arrs["I"].tolist(), arrs["O"].tolist()
+    theta, bias = arrs["theta"].tolist(), arrs["bias"].tolist()
+    s = [0] * H
+
+    def feed(sym, mode, s):
+        for p in range(RT.TICKS):
+            x = [0] * RT.D_IN
+            x[sym] = x[mode] = x[RT.PHASE0 + p] = 1
+            s = RT.reference_step(R, I, theta, s, x)
+        return s
+    s = feed(RT.BOS, RT.MODE_PREFIX, s)
+    for b in payload:
+        s = feed(b, RT.MODE_PREFIX, s)
+    cur, out = RT.SEP, []
+    while len(out) < max_symbols:
+        s = feed(cur, RT.MODE_OUTPUT, s)
+        sc = RT.reference_scores(O, bias, s)
+        y = max(range(RT.V), key=lambda o: (sc[o], -o))
+        out.append(y)
+        if y == RT.EOS:
+            return {"status": "eos", "symbols": out}
+        if y >= 256:
+            return {"status": "invalid_symbol", "symbols": out}
+        cur = y
+    return {"status": "no_eos_within_cap", "symbols": out}