Bibliographic record
Abstract
Les chutes de neige superieures a 10 cm en Alberta sont habituellement associees a l'ascendance a grande echelle qui se produit a l'interieur d'une depression ondulatoire, et la quantite maximale de neige depend de la quantite maximale de vapeur d'eau disponible pour les precipitations. En vertu du principe de conservation de l'eau, la chute de neige maximale est liee au rapport de melange de saturation de la vapeur aux niveaux de la base et du sommet des nuages. Les incertitudes inherentes aux donnees d'entree permettent des approximations numeriques menant a une relation lineaire entre la chute de neige maximale et la temperature de la base des nuages. Pour tester la validite de la relation lineaire chute de neige-temperature, on a analyse la correlation entre les mesures des chutes de neige en 24 heures et les observations de temperature dans les sondages realises en amont. L'ensemble de donnees couvrait toute l'Alberta (sauf la region montagneuse de l'ouest) durant la periode d'octobre 1990 a avril 1993. Selon ces donnees, les quantites de neige semblent montrer une dependance approximativement lineaire avec la temperature a 850 mb, avec un coefficient de correlation de 0,62. Nous nous sommes aussi demandes si la relation chute de neige-temperature peut etre utilisee comme complement a la prevision quantitative des precipitations (PQP) employee dans les modeles de prevision meteorologique numerique (PMN). En particulier, la relation chute de neige-temperature s'est averee plus interessante que la sortie du modele du Centre europeen pour les previsions meteorologiques a moyen terme (CEPMMT). On discute des consequences de ces resultats sur la prevision des fortes chutes de neige en Alberta.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".