CodonTrace Genesis

A world small enough to replay, and a claim strict enough to refuse itself.
Research software. Not a proof of intelligence, and not a biological result.

CodonTrace Genesis is a laboratory you can run twice and get the same world back.

You set down a small place. Simple agents eat, survive, and reproduce. The energy of each birth comes out of the parent. The questions are evolutionary: does an antagonist push a lineage somewhere new, does a costly behavior hold its ground, does a line recover after its path is cut. The library exists so those questions can be asked without the answer being talked into shape afterwards. A birth names its parent. A checkpoint is the moment it was taken, not whatever the run became later. A number is stored beside the only scope it is allowed to have.

The aim is not to announce a Red Queen, an open-ended mind, or a medical device. The aim is a digital-evolution engine whose ledgers, forks, and verdicts stay weaker than the temptation to overclaim them. Four words are allowed at the end of a test, and only one of them is support, and only inside the model that was actually run: SUPPORTED_IN_MODEL, FALSIFIED_IN_MODEL, INCONCLUSIVE, BLOCKED_MEASUREMENT. On the standing ledger, the Red Queen is not proved.

Domain modules sit beside that life-loop. They do not replace it. The installable package is codontrace. Product naming for contributors lives in CONTRIBUTING.md and STYLE.md.

How to read a result

A number in this repository is not a conclusion. A standing verdict is one of four words, and only one of them may be attached to a test:

SUPPORTED_IN_MODEL · FALSIFIED_IN_MODEL · INCONCLUSIVE · BLOCKED_MEASUREMENT

The single source for the 29 September 2026 program is docs/experiments/2026-09-29/VERDICT_LEDGER_V1.json. On that ledger hypothesis_supported is false and red_queen_proved is false. The confirmatory campaign is not open. A green workflow is not a scientific result: the lint and typecheck job is continue-on-error, so a green run is not a mypy pass.

Van Valen’s Red Queen (1973) is the biological hypothesis these records are about. None of them establishes it, in the model or outside it. Open-ended intelligence and a Tokyo Type 1 pass (Channon 2024) stay blocked. Measurement of a trajectory is not a pass.

Figure style

Figures in this file use one palette. A later diagram should reuse these parameters rather than invent a second visual language.

%%{init: {'theme':'base','themeVariables': {'primaryColor':'#e7eef8','primaryTextColor':'#142033','primaryBorderColor':'#1f4e79','lineColor':'#1f4e79','secondaryColor':'#f3efe6','tertiaryColor':'#f7f5f0','fontFamily':'ui-sans-serif, system-ui, sans-serif','fontSize':'15px'}}}%%
flowchart LR
  world["World tick<br/>eat, survive, reproduce"] --> ledger["Ledgers<br/>energy, contact, birth, death"]
  ledger --> freeze["Checkpoint<br/>frozen at capture"]
  freeze --> digest["Digest<br/>recomputed on read"]
  digest --> gate["Claim gate<br/>scope written beside the number"]
  gate --> verdict["One standing verdict"]

The path above is an engineering path. Reaching the last box does not promote the run.

%%{init: {'theme':'base','themeVariables': {'primaryColor':'#e7eef8','primaryTextColor':'#142033','primaryBorderColor':'#1f4e79','lineColor':'#1f4e79','secondaryColor':'#f3efe6','tertiaryColor':'#f4e4dc','fontFamily':'ui-sans-serif, system-ui, sans-serif','fontSize':'15px'}}}%%
flowchart TB
  unit["One unit<br/>history, seed, run, intervention"] --> interval["Student-t interval<br/>defined, and not covering zero"]
  interval --> floor["At least 16 independent units<br/>the ClaimGate seed floor"]
  floor --> isolated["Isolation verified<br/>settings differ only on the target factor"]
  isolated --> allowed["Eligible to be discussed as in-model support"]
  allowed --> blocked["Still blocked<br/>AGI, consciousness, Tokyo Type 1 pass,<br/>biological Red Queen proved"]
  classBlocked["A checkpoint of the same unit"] -.-> unit
  slopeBlocked["A non-zero slope, with no own-lag baseline"] -.-> blocked

Hurlbert (1984) is the reason a checkpoint is not a second replicate. Granger (1969) is the reason a slope is not a predictive gain: the comparison is a restricted regression on the target’s own lag against an unrestricted regression that also includes the source. This library reports the fractional drop in residual sum of squares. It does not report an F test, and an empty control list leaves the result a confounded_candidate.

What the current model refuses to mix up

These are contracts of the software. They are not findings about organisms.

The historical estimators stay in the tree so an old number can be reproduced and then not reused as the corrected estimand. A locked WAVE classifier that still reads pass_prelim does not set red_queen_proved.

What it is

• A Python research library for controlled digital-evolution and artificial-life experiments.
• A replay and audit layer: specs, runtime digests, manifests.
• Mechanism instrumentation: ablations, treatment and control, delayed outcomes.
• A claim-gated workflow. A software capability and a runtime observation are allowed. A strong scientific conclusion is not auto-promoted.
• One biomedical port and one hardware arm on that same auditor. Further modules attach without a second engine.

What it is not

CodonTrace Genesis is not currently presented as:

• proof of artificial general intelligence, consciousness, or collective intelligence
• proof of open-ended intelligence, or a Tokyo Type 1 pass (Channon 2024)
• a biological evolution simulator or a wet-lab chemistry engine
• a replacement for Avida (Ofria and Wilke 2004), MABE, DEAP, QDax, or pyribs
• a physical-robot platform (SimEsp32Bridge is an engineering stub)
• a medical device, SaMD, IVD, FDA or CE clearance, or an ASME V&V 40 certification
• an Avida or MABE campaign runner (those ClaimGate adapters stay skeletons until audited published tables exist)

Claims have to pass evidence gates. See CLAIMS.md and docs/WHY_NOT_INTELLIGENCE_YET.md.

Status

Phases A–L

Phases A–G are the earlier 0.3.0b3 substrate. Phases H–L, HE01 SCHEMA v7, and the discovery ClaimGate pipeline shipped in public 0.3.0b4.

Still blocked: bare collective_intelligence, intelligence, AGI, tokyo_type1_passed, and Avida replacement. Smoke never sets ClaimGate flags. Digests are never invented.

Installation

Python 3.11–3.14. CI smokes Ubuntu, Windows, and macOS on that range. The published wheel is codontrace==0.3.0b18. An editable install of main prints 0.3.0b18.

pip install codontrace==0.3.0b18

pip install "codontrace[research]==0.3.0b18"
pip install "codontrace[causal]==0.3.0b18"
pip install "codontrace[qd]==0.3.0b18"

From source, which may be ahead of PyPI:

git clone https://github.com/Parvaz-Jamei/codontrace-genesis.git
cd codontrace-genesis
python -m pip install -e ".[dev,research,causal,qd]"
python -c "import codontrace; print(codontrace.__version__)"

Do not treat the version tuple as a phase fence, and do not tag or publish from a red or queued CI.

Quick start

The beginner API returns the agent, the world, the trace, and an optional explanation.

from codontrace import WhiteBoxAgent, World2D

world = World2D.from_ascii("""
....
.A*.
....
""")

agent = WhiteBoxAgent.from_world(world, genome="101111000", initial_atp=5.0)
result = agent.run_trial(world, steps=3, explain=True)

print(result.agent.position)
print(result.explanation.summary if result.explanation else "no explanation")

A research run uses an explicit spec. Empty research defaults are not a life-loop: ResourceConfig.density=0 and a same-cell reproduction rule do not make a Darwinian substrate. Use the preset.

from codontrace.genesis import GenesisEngine, GenesisRuntimeProfile

spec = GenesisRuntimeProfile.life_loop_world(seed=7, tick_count=12, population=6)
result = GenesisEngine.from_spec(spec).run_ticks()
print(result.digest()[:24])

Opt-in presets (sexual recombination, fluctuating environments, multi-generation measurement, materials, and the H–L harnesses) stay off unless requested, so earlier digest pins remain stable. Print-only smokes live under examples/.

Console

The console is a local preview module. It does not run the evolution engine, it does not execute an uploaded .py file, and it does not set red_queen_proved. A gate row is the catalog plus the latest preview in the browser, not a pytest pass. On startup, and again every 24 hours, it asks GitHub whether a newer release exists. That query does not push. A clean checkout of this repository can fast-forward; a wheel install is left as it is.

The same command works on Linux, Windows, and macOS after a normal install. No extra package and no Node process are required to open the page.

python -m codontrace.console

The default address is http://127.0.0.1:8765/. --host and --port change the bind. --open asks the desktop to open the page. Workers stay in 1–4. A temperature is reported only when the machine exposes a sensor file. Windows does not have a load average, so that field stays unmeasured there.

The page source lives in console/. Rebuild it with Node only when the interface itself changes; the result is stored under src/codontrace/console/static and shipped inside the wheel. The server is codontrace.console and does not import engine.py.

Claim policy

ScientificClaimGate can allow collective_intelligence_candidate only when the full honest flag set is present, including replay. It does not allow bare collective_intelligence, intelligence, AGI, tokyo_type1_passed, or Avida replacement. Policy: CLAIMS.md. Ladder: docs/protocol/CLAIM_LADDER_PROTOCOL_v0.1.md.

Architecture

The product is the engine. It does not know medicine or hardware. A new module is a DomainProfile or an adapter. It is not a copy of the engine.

%%{init: {'theme':'base','themeVariables': {'primaryColor':'#e7eef8','primaryTextColor':'#142033','primaryBorderColor':'#1f4e79','lineColor':'#1f4e79','secondaryColor':'#f3efe6','tertiaryColor':'#f7f5f0','fontFamily':'ui-sans-serif, system-ui, sans-serif','fontSize':'15px'}}}%%
flowchart TB
  engine["GenesisEngine<br/>ticks, digest, replay"] --> bundle["claimgate_bundle_v1"]
  bundle --> audit["audit_bundle"]
  audit --> ladder["Ladder 0–5<br/>no forbidden alias"]
  bio["Biomedical DomainProfile<br/>declared evidence table"] --> audit
  hw["Hardware arm<br/>SimEsp32Bridge"] --> audit
  foreign["Avida .dat or MABE CSV<br/>read-only adapter"] --> audit

ALIFE is the default profile. BIOMEDICAL and HARDWARE are the two extra profiles that ship now. The biomedical port stores ASME V&V 40, FDA 2023, IEC 62304, and IMDRF wording as labels. It ranks a phenomena table and caps a coupled model at its weakest submodel. A study file closes a phenomenon only when that arm was executed. A typed rank does not. Declared model risk has its own bar. The bar does not move the claim ladder. Strings such as asme_vv40_passed, fda_cleared, and samd_certified raise ConfigurationError. This is not SaMD.

from codontrace.claimgate import audit_bundle
from codontrace.claimgate.adapters.codontrace import bundle_from_hard_experiment_01

report = audit_bundle(bundle_from_hard_experiment_01())
print(report.achieved_level, report.public_name, report.missing_for_next)

from codontrace.claimgate import audit_bundle
from codontrace.claimgate.adapters.biomedical import bundle_from_device_model_cou

bundle = bundle_from_device_model_cou(
    question_of_interest="Would this score table support the claim?",
    context_of_use="Declared table only; no implant.",
    model_influence=2,
    decision_consequence=3,
    treatment_scores=(0.12, 0.11, 0.13),
    control_scores=(0.20, 0.19, 0.21),
    device_software_kind="simd_declared",
    iec_62304_class="B",
    imdrf_n12_category="II",
    fda_2023_evidence=(1, 3, 8),
    physics_based=True,
)
print(audit_bundle(bundle).achieved_level, bundle.extra["domain"], bundle.extra["model_risk"])

The second call stays on the biomedical port. It does not start the engine. Map: docs/ARCHITECTURE_PORTS.md. Biomedical scope: docs/BIOMEDICAL_ENGINEERING.md. Replay contract: docs/ENGINE_REPLAY_CONTRACT.md.

Documentation

The benchmark smoke is a functionality check. It is not evidence of collective intelligence.

python -m pytest tests/examples/test_collective_joss_evidence_benchmark_smoke.py -q

Testing

python -m compileall -q src tests examples tools
python -m pytest tests/genesis_gates -q
python -m pytest tests/science_gates -q
python -m pytest tests -q

The full suite is what CI runs. Tiers: REPRODUCIBILITY.md.

Citation

Cite the versioned software release. The DOI is the software archive, not a campaign archive.

@software{codontrace_genesis_2026,
  title = {CodonTrace Genesis},
  author = {Jamei, Parvaz},
  version = {0.3.0b18},
  doi = {10.5281/zenodo.20337435},
  url = {https://github.com/Parvaz-Jamei/codontrace-genesis},
  note = {0.3.0b18 is the git identity. Cuts 0.3.0b4 through 0.3.0b17 are not recut. The DOI is the software archive, not a campaign archive.}
}

CITATION.cff is included for citation tools. Use of the software does not imply co-authorship.

Works named above

These are the sources the contracts are answerable to. Naming them is not a claim that this repository has reproduced them.

• Granger, C. W. J. 1969. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37:424–438.
• Hurlbert, S. H. 1984. Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54:187–211.
• Ofria, C., and C. O. Wilke. 2004. Avida: a software platform for research in computational evolutionary biology. Artificial Life 10:191–229.
• Student. 1908. The probable error of a mean. Biometrika 6:1–25.
• Van Valen, L. 1973. A new evolutionary law. Evolutionary Theory 1:1–30.

License

CodonTrace Genesis is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0-or-later), so that modified, redistributed, and network-deployed versions stay inspectable.

Commercial or proprietary use that cannot comply with that license may contact the author for a separate license.

See LICENSE and NOTICE.

Author

Parvaz Jamei

GitHub: @Parvaz-Jamei

CodonTrace Genesis — replayable evidence for digital evolution. A run is not a verdict.