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Record W3162277664 · doi:10.35985/9789585522947.6

Bienestar y salud en la Institución Universitaria Escuela Nacional del Deporte

2018· book-chapter· es· W3162277664 on OpenAlexaboutno aff
José Antonio Correa Martínez, Isabel Cristina Selada Aguirre

Bibliographic record

VenueUniversidad Santiago de cali eBooks · 2018
Typebook-chapter
Languagees
FieldHealth Professions
TopicHealth and Lifestyle Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

“Bienestar y Salud en la Institución Universitaria Escuela Nacional del Deporte” es un programa dirigido a funcionarios, administrati-vos y docentes, implementado por la Unidad de Bienestar Universitario en articulación con la Unidad de Desarrollo humano, que tiene como objetivo la promoción de la salud y prevención de enfermedades relacionadas con el sedentarismo y el entorno laboral, el cual es coherente con la visión de la Organización Mundial de la Salud, la Carta de Ottawa, el Plan Decenal de Salud Pública 2012 -2021, el Plan Nacional de Salud Ocupacional 2013-2021 y las políticas Institucionales emanadas del Plan Indicativo 2015-2019 en los proyectos “Fomento de una cultura en salud de auto cuidado físico y psicológico en la comunidad universitaria” y “Promoción de actividades deportivas y recreativas para la comunidad universitaria”. En cumplimiento de lo anterior, durante la vigencia 2017-1, se desarrollaron diversas actividades como las pausas saludables con una frecuencia de 700 sesiones, el taller de buceo que pasó de 12 usuarios en la vigencia 2017-1 a 20 usuarios en la vigencia 2017-2; encuentros de bolos con una cobertura de 174 asistentes, y cami-natas ecológicas a senderos y reservas naturales de la ciudad Cali, el cual alcanzó un número de 51 participantes.

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)0.004
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.159
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0070.002
Scholarly communication0.0050.003
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0360.006

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 head0.031
GPT teacher head0.327
Teacher spread0.297 · 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
GenreOther

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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