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Field connection mapping and systematic ideation for method transfer
Passed 22 of 23 test cases with the skill, and 19 of 23 without it.
and 1 more in the full report
3 fixed19 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
In high-dimensional sparse regression, penalized regression induces sparsity. Which signal processing technique provided the conceptual transfer underlying L1-penalized regression?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies basis pursuit in signal processing as the origin of Lasso. | Missed | Passed |
| Explains L1 norm regularization as a convex relaxation of L0 norm. | Missed | Passed |
The instructions your model reads when the skill loads.
Systematic framework for discovering statistical innovations through cross-field connections
Use this skill when: brainstorming new methods, seeking novel approaches to statistical problems, looking for inspiration from other fields (physics, CS, biology, economics), or wanting to apply techniques from one domain to another.
Many statistical breakthroughs originated elsewhere:
| Statistical Method | Origin Field | Transfer |
|---|---|---|
| MCMC | Physics (Metropolis) | Statistical computation |
| Boosting | Machine learning | Ensemble methods |
| Lasso | Signal processing | Sparse regression |
| Optimal transport | Mathematics | Distribution comparison |
| Neural networks | Neuroscience/CS | Flexible function estimation |
| Causal graphs | Philosophy/AI | Causal inference |
Problem in Statistics → Abstract Structure → Search Other Fields
↑ ↓
Validate/Adapt ←── Identify Analogues ←── Find Connections
| ML Method | Statistical Application | Transfer Opportunity |
|---|---|---|
| Double ML | Debiased mediation effects | Nuisance parameter estimation |
test cases passed, vs 19 / 23 without
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