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Record W2152514602 · doi:10.1136/bjsports-2014-093561

Time for change: a roadmap to guide the implementation of the World Anti-Doping Code 2015

2014· article· en· W2152514602 on OpenAlexaff
Jiří Dvořák, N Baume, Francesco Botrè, Julian Broséus, Richard Budgett, Walter O. Frey, Hans Geyer, Peter Harcourt, Dave Ho, David Howman, Victor Isola, Carsten Lundby, François Marclay, Annie Peytavin, Andrew Pipe, Yannis Pitsiladis, Christian Reichel, Neil Robinson, Г. М. Родченков, Martial Saugy, Souheil Sayegh, Jordi Segura, Mario Thevis, Alan Vernec, Marjolaine Viret, Marc Vouillamoz, Mario Zorzoli

Bibliographic record

VenueBritish Journal of Sports Medicine · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsWorld Anti-Doping Agency
Fundersnot available
KeywordsAgency (philosophy)Public relationsMedicinePolitical scienceComputer sciencePsychologySociology

Abstract

fetched live from OpenAlex

A medical and scientific multidisciplinary consensus meeting was held from 29 to 30 November 2013 on Anti-Doping in Sport at the Home of FIFA in Zurich, Switzerland, to create a roadmap for the implementation of the 2015 World Anti-Doping Code. The consensus statement and accompanying papers set out the priorities for the antidoping community in research, science and medicine. The participants achieved consensus on a strategy for the implementation of the 2015 World Anti-Doping Code. Key components of this strategy include: (1) sport-specific risk assessment, (2) prevalence measurement, (3) sport-specific test distribution plans, (4) storage and reanalysis, (5) analytical challenges, (6) forensic intelligence, (7) psychological approach to optimise the most deterrent effect, (8) the Athlete Biological Passport (ABP) and confounding factors, (9) data management system (Anti-Doping Administration & Management System (ADAMS), (10) education, (11) research needs and necessary advances, (12) inadvertent doping and (13) management and ethics: biological data. True implementation of the 2015 World Anti-Doping Code will depend largely on the ability to align thinking around these core concepts and strategies. FIFA, jointly with all other engaged International Federations of sports (Ifs), the International Olympic Committee (IOC) and World Anti-Doping Agency (WADA), are ideally placed to lead transformational change with the unwavering support of the wider antidoping community. The outcome of the consensus meeting was the creation of the ad hoc Working Group charged with the responsibility of moving this agenda forward.

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)0.112
metaresearch head score (Gemma)0.165
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.112
Threshold uncertainty score0.594

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1120.165
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0120.005
Science and technology studies0.0120.009
Scholarly communication0.0300.030
Open science0.0110.033
Research integrity0.0270.028
Insufficient payload (model declined to judge)0.0330.016

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 head0.030
GPT teacher head0.376
Teacher spread0.347 · 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
GenreCommentary

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

Citations32
Published2014
Admission routes1
Has abstractyes

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