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Record W2249886333

La densité de population et le climat effets sur le dimorphisme sexuel, la masse corporelle et les changements saisonniers de masse du mouflon d'Amérique (Ovis canadensis)

2001· article· fr· W2249886333 on OpenAlexaboutno aff
Mylène LeBlanc

Bibliographic record

VenueKnowledge UdeS (Institutional Deposit of the University of Sherbrooke) · 2001
Typearticle
Languagefr
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsForestryGeographyPopulationDemographySociology
DOInot available

Abstract

fetched live from OpenAlex

Les objectifs de mon étude étaient donc d'examiner comment des facteurs extrinsèques à l'individu tels que la densité de population et le climat peuvent affecter la masse corporelle individuelle et les changements en masse des différentes classes de sexe et d'âge d'un ongulé de montagne, le mouflon d'Amérique. L'étude a été réalisée à partir de la base de données à long terme de la population de Ram Mountain, Alberta. Le suivi à long terme de cette population a permis de recueillir des données sur la masse corporelle des individus ainsi que sur les variations saisonnières de masse s'échelonnant sur plus d'une vingtaine d'années. Le premier but de cette étude était de tester l'hypothèse présumant que l'augmentation de la taille de la population a un effet négatif sur la croissance et la masse corporelle et que ces effets sont différents pour les mâles et les femelles. Le deuxième but de mon travail consistait à vérifier les effets d'un deuxième facteur susceptible d'avoir un effet important sur la masse et ses variations: le climat."--Résumé abrégé par UMI

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.196
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

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