Resurfice, Clements & Ediger: une trilogie en matière de causalité factuelle (Resurfice, Clements & Ediger: A Trilogy in Factual Causation)
Bibliographic record
Abstract
Fench Abstract: Mathieu Demilly est avocat au cabinet Juristes Power a Ottawa. Il est diplome de l’Institut d’etudes politiques de Rennes et possede une maitrise en economie de l’Universite de Rennes. Il a complete son JD au Programme de common law en Francais de l’Universite d’Ottawa et a effectue son stage professionnel du barreau au sein de Heenan Blaikie s.r.l. et Juristes Power.English Abstract: Mathieu Demilly is an associate at the Ottawa office of Power Law. He graduated from the Institut d’etudes politiques de Rennes and has a Masters in Economics from the University of Rennes. He completed his JD at the French Common Law Program of the University of Ottawa and articled with Heenan Blaikie LLP and with Power Law.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.036 |
| Scholarly communication | 0.008 | 0.020 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".