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Record W2093193882 · doi:10.1136/bjsports-2014-093653

Drawing the map to implement the 2015 World Anti-Doping Code

2014· editorial· en· W2093193882 on OpenAlexaff
Jiří Dvořák, Richard Budgett, Martial Saugy, Alan Vernec

Bibliographic record

VenueBritish Journal of Sports Medicine · 2014
Typeeditorial
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsWorld Anti-Doping Agency
Fundersnot available
KeywordsCode (set theory)Computer scienceMedicineInformation retrievalData scienceWorld Wide WebProgramming language

Abstract

fetched live from OpenAlex

As of 1 January 2015, the revised 2015 World Anti-Doping Code will be operational in the fight against doping. This will be binding for all stakeholders who unanimously approved the revised code at the ‘World Conference on Doping in Sport’ in Johannesburg, South Africa on 15 November 2013. Following this, a medical and scientific multidisciplinary consensus meeting on antidoping in sport was held at the home of FIFA, Zurich, Switzerland from 29 to 30 November 2013. The aim was to create a road map to implement …

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)0.016
metaresearch head score (Gemma)0.070
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.024
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.070
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.002
Science and technology studies0.0050.005
Scholarly communication0.0130.010
Open science0.0030.004
Research integrity0.0200.033
Insufficient payload (model declined to judge)0.0240.015

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 head0.017
GPT teacher head0.342
Teacher spread0.325 · 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
GenreEditorial

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

Citations5
Published2014
Admission routes1
Has abstractyes

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Same venueBritish Journal of Sports MedicineSame topicDoping in SportsFrench-language works237,207