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Record W2968509025 · doi:10.3917/infle.019.0067

Dopage et conduites dopantes

2012· article· fr· W2968509025 on OpenAlexaff
André‐Xavier Bigard, Alexandra Malgoyre, Hervé Sanchez

Bibliographic record

VenueInflexions · 2012
Typearticle
Languagefr
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Le recours à des produits, substances ou techniques susceptibles d’améliorer les performances physiques ou psychiques est très fortement ancré dans la nature humaine. Les autorités de santé et sportives identifient des produits dont l’usage est interdit chez les sportifs, et disposent d’un arsenal juridique permettant de limiter leur utilisation. Ces décisions sont prises afin de préserver l’état de santé des sportifs et l’éthique du sport. En opérations, l’utilisation de certains de ces produits est envisageable dans un cadre réglementaire bien défini, et avec une parfaite traçabilité. En revanche, les conduites dopantes ne bénéficient d’aucune disposition réglementaire les limitant. En milieu militaire d’importants efforts d’information doivent être faits afin de convaincre de l’inutilité de la très grande majorité des produits utilisés.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.072
GPT teacher head0.384
Teacher spread0.312 · 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 designQualitative
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
Published2012
Admission routes1
Has abstractyes

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