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Record W2901027180

Évaluation d'un score clinique ("Score Wisconsin") pour le diagnostic des maladies respiratoires des veaux laitiers avant sevrage au Québec

2017· dissertation· fr· W2901027180 on OpenAlexaboutno aff
Charlotte Faure-Caylar

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2017
Typedissertation
Languagefr
FieldAgricultural and Biological Sciences
TopicVector-Borne Animal Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesGynecologyPolitical scienceArtMedicine
DOInot available

Abstract

fetched live from OpenAlex

Les maladies respiratoires des lots de veaux au moment de leurs mise en lots en élevages est une des problématiques les plus difficiles à gérer. La détection et le traitement précoce des malades, voire du lot entier, sont primordiaux. Le score clinique du Wisconsin permet d’évaluer la santé respiratoire des animaux, de manière simple, rapide et non invasive. Le but de cette thèse est d’évaluer si un changement d’opérateur influe sur les notes attribuées aux veaux, afin de savoir si ses résultats sont fiables. Les résultats montrent une grande disparité entre plusieurs opérateurs, au niveau des scores chiffrés attribués aux veaux. Cependant, les résultats sont très proches d’un opérateur à l’autre, en considérant le fait que les animaux soient classés comme « malades » ou « sains » par les résultats du score. Le score clinique est donc assez fiable, et utilisable en élevage par les éleveurs ou les vétérinaires, pour prendre la décision de traiter ou non l’intégralité d’un lot de veaux lorsqu’une partie de ces veaux est malade.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0050.002
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.255
Teacher spread0.210 · 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 teacher head, not a consensus.

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueHAL (Le Centre pour la Communication Scientifique Directe)Same topicVector-Borne Animal DiseasesFrench-language works237,207