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Record W4315781978 · doi:10.46932/sfjdv4n1-004

Hábitos alimentarios en una muestra de estudiantes universitarios de Yucatán

2023· article· es· W4315781978 on OpenAlexaff
Manuel Ordóñez Luna, Guadalupe Andueza Pech, Yolanda Oliva Peña, Andrés Santana Carvajal

Bibliographic record

VenueSouth Florida Journal of Development · 2023
Typearticle
Languagees
FieldHealth Professions
TopicHealth and Lifestyle Studies
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Los estudiantes universitarios son vulnerables a la inadecuada alimentación por la naturaleza de la vida universitaria; necesitan consolidar buenos hábitos alimentarios, los cuales son un factor de importancia para mantener un buen estado de salud y prevenir enfermedades. Para evaluar el consumo de alimentos en estudiantes universitarios, se realizó un estudio transversal en una muestra de 271 estudiantes de 4 Facultades de la Universidad Autónoma de Yucatán. Una tercera parte de los estudiantes desayunó diariamente, en mayor proporción las mujeres y jóvenes de la Facultad de Medicina. El consumo recomendado de frutas, verduras y legumbres, lácteos, pescado y alimentos integrales fue bajo, en cambio hubo elevada ingesta de comida rápida, frituras, galletas y dulces. Es recomendable fomentar programas educativos en alimentación saludable y actividad física que beneficien a la comunidad universitaria como insumo a su formación integral y con el fin de proteger del riesgo de enfermedades no transmisibles en el futuro.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.335

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.032
GPT teacher head0.365
Teacher spread0.333 · 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 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

Citations8
Published2023
Admission routes1
Has abstractyes

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