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Record W7027938812

Doping: efectos sobre el organismo de las principales sustancias y métodos utilizados. Control del dopaje

2014· dissertation· es· W7027938812 on OpenAlexaboutno aff

Bibliographic record

VenueUVaDOC UVaDOC University of Valladolid Documentary Repository (University of Valladolid) · 2014
Typedissertation
Languagees
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsnot available
Fundersnot available
KeywordsControl (management)Field (mathematics)Context (archaeology)Scientific field
DOInot available

Abstract

fetched live from OpenAlex

Esta revisión bibliográfica pone en evidencia el alcance de la ciencia dentro del campo de sustancias y métodos utilizados para falsear la actualidad deportiva. El dopaje está socialmente considerado como un acto vergonzoso, ilegal, injusto y antiético. La Agencia Mundial Antidopaje (AMA) o WADA (World Anti – Doping Agency) es una organización internacional e independiente, que se encarga de promover, coordinar y supervisar la lucha contra el dopaje deportivo en todas sus formas. Tiene su sede en Montreal (Canadá). Mediante un acuerdo de todos los países que forman parte de la AMA, se ha elaborado una lista oficial de sustancias y métodos prohibidos en el deporte. Las principales sustancias utilizadas como dopantes son esteroides, estimulantes, hormona de crecimiento, EPO, beta-2 agonistas, y dentro de los métodos prohibidos cabe mencionar el dopaje sanguíneo y el genético. El control de dopaje comienza con la selección y notificación al deportista seleccionado, dentro o fuera de una competición, la toma de muestra urinaria o sanguínea, el envío al laboratorio donde se realiza el análisis de la muestra y la posterior comunicación de resultados. En casos adversos, se procederá según el reglamento de la entidad que solicitó el control. El Consejo Superior de Deportes, ha aprobado el temario del curso que habilita al personal sanitario para actuar como agentes de control antidopaje En el mundo existen 34 laboratorios homologados y reconocidos por la Agencia Mundial Antidopaje. Dos de éstos laboratorios se encuentran en España.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.216
Teacher spread0.208 · 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; both teacher heads agree on what is shown here.

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
Published2014
Admission routes1
Has abstractyes

Explore more

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