Daughter Machine computational Evaluate
status 1 · Plancomplete 2 · Executionran 3 · Evidence 4 · Quality 5 · Decision 6 · Release Implementationcomplete
Q How do daughter cells track through an open chamber with an absorbing boundary?
Claim
How do daughter cells track through an open chamber with an absorbing boundary?
Test
Result
Model composition
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Analyses to run — which of the workspace's ANALYSIS_REGISTRY entries to compute on dispatch
Runnable models — the composite(s) this study simulates
viva_munk.composites.daughter_machine
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Simulations
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Results
What came back from this study's runs — a per-store preview of the latest run, plus the raw emitter store (zarr/parquet/runs.db) for every run.
Latest run preview
Per-store sparkline + first/last/min/max from the most recent run's emitted trajectory. This is a downsampled PREVIEW, not the full data — use the per-store or Download-all links for the complete arrays.
Analyses
Result files written by this study's analysis steps.
Readouts
The Design-time emit contract: what the emitter is configured to persist, which store paths it declares, and the shape of what lands on disk. No observed values here — see Results for what actually came back from a run.
Emitter & config
The emitter class, its write-path module, emit
interval/buffer, output location, and emit scope — from
lib/emitters.py and this study's (or the workspace's)
runtime.default_emitter.
Emitted paths
Each row is an emitter store_path
the composite will save; authored entries in study.yaml add names,
descriptions, and units on top.
Outputs & shapes
Store path, dtype, shape
(n_steps, …), units, and a best-effort byte estimate for each emitted
leaf.
Tests
The bar. What must be true for this model to count as correct — the acceptance criteria, their bands, and the report cards that grade them.
Report cards
The compiled output of this study’s Tests — per-test verdict and the change since the previous run.
Behavioral tests
true
data_source: latest_run
- No
expected_behavior:entries declared in study.yaml yet. Add some to see them appear here as test rows. Click "Run tests" to discover and execute additionalstudies/<slug>/tests/test_*.pyfiles alongside the auto-generated assertions.
Audit
Is the bar sound? Whether the tests themselves are rigorous and matched to the problem — sufficiency, where the model was sourced, and the rigor + reproducibility scorecards.
Build
Was it earned? The agentic model-building loop that iterated the model to clear the bar — the draft, the frozen tests, the iteration-by-iteration trajectory, and the result (or an honest give-up).
Verdict & conclusion
○ unattributed
🔒 frozen 2026-09-24 02:12 UTC ·
21ebac1a8f