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Record W7104249754 · doi:10.5281/zenodo.17543509

ESTIMACIÓN INDIRECTA DEL GASTO ENERGÉTICO, COMPOSICIÓN CORPORAL Y CAPACIDAD AERÓBICA EN ESTUDIANTES UNIVERSITARIOS DE ENTRENAMIENTO

2025· article· W7104249754 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldBusiness, Management and Accounting
TopicBusiness, Education, Mathematics Research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Quarter (Canadian coin)AttendanceTime budgetWork (physics)

Abstract

fetched live from OpenAlex

El presente estudio analizó el perfil fisiológico de 364 estudiantes del programa de Tecnología en Entrenamiento Deportivo de una institución universitaria, mediante la estimación indirecta de variables de composición corporal, metabolismo basal y capacidad cardiorrespiratoria. Los datos fueron obtenidos durante actividades académicas prácticas correspondientes a cinco grupos de la asignatura Fisiología del Ejercicio. Se emplearon ecuaciones predictivas validadas para estimar indicadores como el porcentaje de grasa corporal, la tasa metabólica basal (BMR), el gasto energético total (TDEE) y el consumo máximo de oxígeno (VO₂máx). Los resultados mostraron diferencias significativas entre hombres y mujeres en variables como masa magra, BMR y TDEE, evidenciando patrones fisiológicos diferenciados por sexo. Asimismo, se identificaron relaciones significativas entre la edad, el porcentaje de grasa corporal y la capacidad aeróbica. Los hallazgos proporcionan bases relevantes para fortalecer estrategias pedagógicas y de seguimiento físico en el contexto académico deportivo.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.618
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0060.001
Scholarly communication0.0040.002
Open science0.0030.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0210.010

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 head0.022
GPT teacher head0.243
Teacher spread0.222 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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