La prise de décisions éclairées et l'entretien préventif
Bibliographic record
Abstract
L'entretien préventif, comme tout ce qui se fait de fil en aiguille, exerce un attrait naturel sur les gens qui s'occupent d'infrastructure. C'est cet attrait qui explique en partie la popularité d'un guide d'introduction récent sur l'entretien préventif des routes municipales, affirme Mike Sheflin, président du Comité technique de chaussées et trottoirs pour le Guide national pour des infrastructures municipales durables (InfraGuide). Le guide d'introduction a été publié il y a 18 mois et est le premier de la série grandissante de rapports d'InfraGuide sur les régles de l'art dans le domaine des infrastructures routières. En effet, six autres documents ont été publiés depuis, traitant de sujets aussi variés que le drainage des routes et le colmatage des fissures dans la chaussée
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".