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Record W1988027533 · doi:10.1016/j.gaceta.2014.04.004

Consumo de riesgo de alcohol y factores asociados en adolescentes de 15 a 16 años de la Cataluña Central: diferencias entre ámbito rural y urbano

2014· article· es· W1988027533 on OpenAlexaff
Núria Obradors-Rial, Carles Ariza, Carles Muntaner

Bibliographic record

VenueGaceta Sanitaria · 2014
Typearticle
Languagees
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAlcohol consumptionResidenceRural areaMedicineHumanitiesDemographyAlcoholArtSociology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence of risky alcohol consumption and associated risk factors among adolescents living in Central Catalonia (Spain) during the 2011-2012 academic year, depending on their area of residence. METHOD: A cross-sectional study was carried out in a sample of 1268 10th grade students (4th grade of secondary education) in Central Catalonia. RESULTS: Risky alcohol consumption was higher among adolescents in rural areas than in urban areas (59.6% versus 49.8%). Associated risk factors were drunkenness in siblings and friends, having positive expectations of alcohol consumption, and buying alcohol. Not living with both parents and poorer academic achievement were associated risk factors in rural areas, while higher socioeconomic status was a risk factor in urban areas. CONCLUSIONS: Risky alcohol consumption was much higher among adolescents living in rural areas. The main associated factor was alcohol consumption among family and friends.

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)0.001
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 score0.207
Threshold uncertainty score0.412

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.269
Teacher spread0.259 · 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

Citations31
Published2014
Admission routes1
Has abstractyes

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