Prédiction de la sélection du microhabitat chez les juvéniles du saumon de l'Atlantique (Salmo salar) à l'aide de la régression logistique et des arbres de classification
Bibliographic record
Abstract
L'auteur de ce mmoire ou de cette thse a autoris l'Universit du Qubec Trois-Rivires diffuser, des fins non lucratives, une copie de son mmoire ou de sa thse.Cette diffusion n'entrane pas une renonciation de la part de l'auteur ses droits de proprit intellectuelle, incluant le droit d'auteur, sur ce mmoire ou cette thse.Notamment, la reproduction ou la publication de la totalit ou d'une partie importante de ce mmoire ou de cette thse requiert son autorisation. Avant-proposCe mmoire comprend deux chapitres.Le premier chapitre est une synthse en franais du projet de matrise.Le second chapitre est l'article soumis pour publication dans le priodique Freshwater Bi%gy.Cet article compare la capacit de deux approches quantitatives, la rgression logistique et les arbres de classification, prdire l'utilisation du microhabitat et la distribution estivale des juvniles du saumon de l'Atlantique, Sa/ma sa/ar.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".