EXPERIMENT REGISTRY · RESULTS AND PROTOCOLS

Scores with
their context.

Every entry states its question, environment, limits, and reproduction path. A benchmark specification without an execution is not a score; scores across different tasks, versions, and models are not comparable.

2published evaluation reports
5local experiments summarized
3topology protocols pending
RESULTS AND EXPERIMENTS

What the runs
measured.

The figures below come from reports and artifacts in the source repository. Task contexts and datasets differ; do not compare scores across them.

01 / REPORTED EVALUATION

LoCoMo · conversational memory

Evaluation of GenOS V3 and Qwen 2.5 Coder 7B on the LoCoMo corpus, with 1,986 questions across five categories.

18.39%Overall F1 · 1,986 questions
23.68%F1 · factual questions (cats. 1–4)
5.84%Overall exact match
QUESTION
What absolute recall score did this GenOS configuration achieve on LoCoMo? No same-model raw-context ablation was reported.
ENVIRONMENT
GenOS V3 · Qwen 2.5 Coder 7B · LoCoMo corpus (1,986 questions)
LIMITS
By category: event 30.71%, factual 17.02%, causal 16.92%, temporal 13.23%, adversarial 0.09%. The adversarial score penalizes explicit refusals when the gold answer is “undefined”; the report proposes a separate abstention metric.
REPRODUCTION
See the LoCoMo report for corpus version and harness commit.
Read the LoCoMo report↗
02 / PARTIAL DATASET EVALUATION

SWE-bench Lite · bug resolution

Run under WSL Ubuntu 24.04 with DeepSeek Coder V2. The report covers tasks ready in the environment, not the entire benchmark.

9 / 26Tasks resolved
34.6%Of 26 ready tasks
300Tasks in the full dataset
QUESTION
Can GenOS resolve real bug-fix tasks end to end?
ENVIRONMENT
WSL Ubuntu 24.04 · DeepSeek Coder V2 · 26 ready tasks of 300
LIMITS
Fixes are validated with FAIL_TO_PASS and PASS_TO_PASS tests. The 26-task denominator limits the scope: this rate is not a result on all 300 SWE-bench Lite tasks.
REPRODUCTION
FAIL_TO_PASS + PASS_TO_PASS validation per the linked report.
Read the SWE-bench Lite report↗
LOCAL EXPERIMENTS AND SIMULATIONS
03 / LOCAL EXPERIMENT · SYNTHETIC

AGOW · diffusion and ablations

Local campaign with Qwen 2.5 Coder 7B: ablation, controlled mediation, and three paired replications on synthetic cases.

11 / 12Success · full diffusion
0 / 12Success · diffusion removed
8 / 8 × 3Replications · diffusion transmitted
QUESTION
Does AGOW diffusion change outcomes on synthetic cases?
ENVIRONMENT
Local campaign · Qwen 2.5 Coder 7B · synthetic cases + 3 paired replications
LIMITS
Workspace ablation scores 11/12 versus 11/12 in this campaign. The same report also documents a Lipson-like run of a simulated trajectory (reward 7.7369) and MBH-RNN (100,000 iterations, ten simulated trials); neither is a replication or a measure of generalization.
REPRODUCTION
Campaign report documents seeds and ablation arms.
Read the campaign report and its limits↗
04 / LOCAL SUITE · 12 TASKS

Planning · policy comparison

A deterministic suite of 12 synthetic tasks compares GenOS with ReAct, Tree of Thoughts, and MCTS, with a budget of 240 expansions.

12 / 12GenOS · tasks passed
11 / 12Tree of Thoughts
24.8Average expansions · GenOS
QUESTION
Does the GenOS planning policy beat ReAct, ToT, and MCTS at equal budget?
ENVIRONMENT
Deterministic harness · 12 synthetic tasks · 240-expansion budget
LIMITS
In this run, ReAct passes 9/12 and MCTS 6/12 (175.9 average expansions). This is a small local synthetic suite, not an independent standard benchmark; a scenario correction was also recorded with the result.
REPRODUCTION
benchmarks/planning-gap/results/2026-09-30-a-star-240.json
View the raw result from September 30↗
05 / DETERMINISTIC ABLATION · 4 SCENARIOS

Self-model ablation

The harness compares eight arms on the same scenarios to check whether removing layers changes the reference decision chain.

6 / 7Layers with an observed effect
4Deterministic scenarios
0Decisions changed · memory here
QUESTION
Which self-model layers affect the reference decision chain?
ENVIRONMENT
Decision harness without LLM · 4 deterministic scenarios · 8 arms
LIMITS
The result depends on a decision harness without an LLM. Effects from some layers remain to be confirmed in runtime missions; the report explicitly distinguishes behavioral change from a status that is merely displayed.
REPRODUCTION
benchmarks/cognitive-key-ablation/README.md
Read the protocol and detailed verdict↗
06 / SIMULATION · EXPLICIT ASSUMPTIONS

Evolution of self mechanisms

Four simulated environments, three seeds, and 40 generations study which layers survive under hypothetical metabolic costs.

4Simulated environments
3Seeds per environment
40Generations
QUESTION
Which layers survive selection under hypothetical metabolic costs?
ENVIRONMENT
Simulation · 4 environments × 3 seeds × 40 generations
LIMITS
Benefit profiles are defined in the model: the experiment informs selection under these assumptions, not an empirical discovery about the mechanisms. The report also flags an uninterpretable contrast in the predictable environment.
REPRODUCTION
Model assumptions and benefit profiles in the linked research doc.
Read the P3 research and its limits↗
07 / STRUCTURAL MEASURE · NO LLM

Cognitive Key · recipe diversity

Ablation on three problems: the harness compares the structural diversity of cognitive recipes composed at dispatch.

3Recipes · diversity arm E
0.51Pairwise distance · E
1.0Requirement coverage · E
QUESTION
Does diversity-arm composition produce structurally varied recipes?
ENVIRONMENT
Ablation harness · 3 problems · no LLM in the loop
LIMITS
Arm D (relevance only) produces one repeated recipe and a distance of 0; E produces three recipes with 1.0 coverage. This result concerns structure, not agent response quality: runtime missions remain to be measured.
REPRODUCTION
benchmarks/cognitive-key-ablation/README.md
Read the protocol, measures, and remaining tasks↗
LIVE TOPOLOGY CAMPAIGN · OUTCOME EVIDENCE

Biocenosis ran.
The missions remain unverified.

12 complex missions used the full local backend and SQLite WAL. 9 cycles blocked and 3 completed; 0 outcomes received verified promotion. This is a functional qualification run, not a comparative benchmark. Its event persistence result does not imply mission success.

INTERACTIVE BENCHMARK · RECORDED RESULTS

Explore all 12 tasks
in one run.

Choose a domain, task and policy to inspect its recorded plan, outcome and expansions from September 30, 2026. This view does not rerun the benchmark.

BLOCKSWORLD · bw-sussman

GenOS A*

GOAL REACHED
YesHarness goal met
3Expansions
2Plan actions
2BFS optimum (if computed)
RECORDED PLAN
  1. 01unstack C
  2. 02stack C on B

Deterministic comparison on synthetic tasks with a 240-expansion cap. These values come from the source runner; this selector does not launch a new run.

SOURCE ARTIFACT · 2026-09-30Download JSON ↗

REPRODUCTION COMMANDnode backend/tests/search/test_planning_gap.jsThe result is specific to this suite, budget and artifact version. Replaying the command requires the GenOS source repository and its environment.

PROTOCOLS WITHOUT CAMPAIGN RESULTS

Ready to measure,
not yet run.

These documents define metrics or experimental plans. They do not provide real comparison results.

—

A-Team

Paired protocol defined; a campaign connected to real workers has not run yet.

↗
—

Longitudinal Holobiont

Twelve-arm protocol; no real campaign has run.

↗
—

Syncytium

Aggregator and metrics are described; campaign counters remain to be collected.

↗
—

EAB · epistemic abstention

The runner awaits the local LoCoMo corpus and complete predictions; no complete EAB report is provided here.

↗
—

SWE-bench Lite · extension

The reported result covers 26 ready tasks, not the full set of 300.

↗
READ BEFORE INTERPRETING

These evaluations reflect the documentation reviewed on 2026-10-18 at GenOS 5091f70. Each result applies only to the tasks, versions, models, and conditions stated in its source. A test result alone does not prove business correctness or generalization.

GenOS evidence principles ↗Explore research areas →