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Record W3164870313

Chapitre 10 - Conception d’études One Health

2020· book-chapter· fr· W3164870313 on OpenAlexfundno aff
Esther Schelling, Jan Hattendorf

Bibliographic record

VenueIndustrias Culturais (Universidade de Coimbra) · 2020
Typebook-chapter
Languagefr
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsnot available
FundersUniversity of AlbertaYork UniversityInternational Development Research CentreMcGill University
KeywordsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Qu’est-ce qu’une étude One Health ? Les études épidémiologiques sur la santé humaine et animale utilisent des enquêtes sur le terrain ou des analyses de données secondaires. La collecte et l’interprétation des données se font traditionnellement dans les secteurs de la santé animale et humaine et à des périodes différentes, mais aussi lorsque le même sujet de santé est abordé, ce qui entraîne une duplication inutile des études sur le terrain. Les études sur les zoonoses et les pathogènes d’or...

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)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.014
Scholarly communication0.0070.007
Open science0.0010.003
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0120.003

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 head0.073
GPT teacher head0.287
Teacher spread0.214 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

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