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ACADEMIC PERFORMANCE AND CONSUMPTION OF ALCOHOL, MARIJUANA, AND COCAINE AMONG UNDERGRADUATE STUDENTS FROM RIBEIRÃO PRETO - BRAZIL

2019· article· en· W2956469204 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicYouth, Drugs, and Violence
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersForeign Affairs and International Trade CanadaGovernment of Canada
KeywordsAlcohol abusePsychologyTest (biology)Clinical psychologyAlcohol consumptionAlcoholMedicinePsychiatryChemistry

Abstract

fetched live from OpenAlex

ABSTRACT Objective: to determine alcohol, marijuana, and cocaine use, abuse, and dependence, and to identify the association between the use of these substances and the academic performance of undergraduate students. Method: a cross-sectional study with 275 undergraduate students from health and humanities courses at a university in Ribeirão Preto, Brazil. The instruments used were the Questionnaire for Screening the Use of Alcohol, Tobacco and Other Substances and the student’s self-report on their performance considering a scale from zero to 10. For analysis, Fisher’s Exact Test and Pearson’s Chi-square test were used. Results: the pattern of alcohol and cocaine use in the sample studied was similar to the national average; however the prevalence of marijuana abuse was higher than the average. The use of marijuana was associated with the students’ academic performance in this study. Conclusion: the same association between abuse of and dependence on marijuana was not identified in the sample studied.

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.247
GPT teacher head0.466
Teacher spread0.219 · 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