license: apache-2.0
pretty_name: Physim Reasoning Tasks
language:
- en
size_categories:
- n<1K
task_categories:
- other
tags:
- reinforcement-learning
- agent-evaluation
- harbor
- biology
- physiology
- simulation
configs:
- config_name: default
data_files:
- split: test
path: task_catalog.jsonl
Physim Reasoning Tasks
Ten whole-body physiology tasks. Each task combines interventions across organ systems and asks an agent to predict downstream changes relative to a matched simulated control. 33 endpoints are scored across the ten tasks: the set was reduced to the endpoints whose simulated direction is defensible from physiology, and the answer keys and graders are unchanged from the released task files.
The task catalog, model comparison, and project overview are available at symbolic.life/tasks.
Contents
tasks/: runnable Harbor tasks, each with an instruction, container environment, verifier, and reference solution.task_catalog.jsonl: browsable task descriptions and prompts.download/: the exact task archive served on symbolic.life.benchmark-results.json: strict whole-task results for every model with a complete run.
Run
Install Docker and uv, then run from this repository’s directory:
uv run --with harbor==0.23.0 python run_verified.py run --path ./tasks --agent oracle
To evaluate an agent, configure its provider credentials in your own environment and run:
uv run --with harbor==0.23.0 python run_verified.py run --path ./tasks --agent terminus-2 --model PROVIDER/MODEL --ak reasoning_effort=high
The supplied launcher uses the tested Harbor version and mounts each task’s verifier separately and read-only. Keep tests/ and solution/ outside the evaluated agent’s environment.
Scoring
The answer gives increase, decrease, or unchanged for each scored output. The task prompt specifies the comparison and the unchanged threshold. The published metric is strict whole-task pass: an attempt counts only when every scored direction in it is correct.
Results
Five attempts per task per model, single-shot with no tools, reasoning effort high. Only models that completed every attempt of every task are listed.
| Model | Attempts passed | Strict pass rate |
|---|---|---|
| Claude Opus 5 | 50/50 | 100.0% |
| Gemini 4 Argon | 43/50 | 86.0% |
| Grok 4.7 | 42/50 | 84.0% |
| Grok 4.6 | 41/50 | 82.0% |
| GPT-6 Astra | 40/50 | 80.0% |
| Thinking Machines Inkling | 35/50 | 70.0% |
| Nemotron 3 Ultra | 20/50 | 40.0% |
Not listed: Claude Opus 5.5 (4 of 10 scenarios; 31 attempts refused by the provider's content filter); Claude Fable 5.1 (3 of 10 scenarios; 35 attempts refused by the provider's content filter); Gemini 3.8 Flash (10 of 10 scenarios but 48 of 50 attempts; 2 refusals).