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Design ablation studies to isolate component contributions in ML systems
Passed 18 of 20 test cases with the skill, and 8 of 20 without it.
and 10 more in the full report
13 fixed8 passed either way2 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
In an ablation study design flow, what is the final step executed in the sequence after sample size estimation?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies statistical method selection as the final step in the execution flow. | Missed | Passed |
The instructions your model reads when the skill loads.
Question: What does each component contribute?
| Ablation Type | Components (N) | Min Runs | When to Use |
|---|---|---|---|
| Systematic (leave-one-out) | 3-8 | N + 2 | Standard component analysis |
| Replacement | 3-8 | 2N + 2 | Need to distinguish "removal" vs "simplification" |
| Combinatorial (selected) | 4-6 | ~2N | Suspected interactions between components |
| Combinatorial (full) | 3-4 | 2^N | Small systems, need complete picture |
| Conditional | 3-6 | N * conditions | Context-dependent contributions |
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|---|
| statistical-method-selection | Select appropriate statistical methods for experiment analysis |
test cases passed, vs 8 / 20 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.