Evaluación Cognitiva Montreal y consumo de alcohol: Un diagnóstico descriptivo del deterioro cognitivo en estudiantes universitarios de Durango, México
Bibliographic record
Abstract
Alcohol is a toxic substance associated with acute and chronic disorders affecting the Central Nervous System and significantly altering brain function. Objective: To determine the relationship between cognitive impairment and alcohol consumption in university students of the Juárez University of the State of Durango. Methodology: It is a cross-sectional, descriptive, comparative, non-probabilistic study, for convenience. A database was designed on the results obtained in a clinical interview on alcohol consumption and the application of the Montreal Cognitive Assessment (MoCA) test. Contribution: The evaluation of cognitive functions show similar results, the male sex presented a better score in Attention and the female one in Orientation. More involvement was identified in the Deferred Memory functions in both groups. In relation to alcohol consumption, the cognitive functions evaluated show lower levels. The female gender was more evident cognitive impairment in relation to alcohol consumption being statistically significant (p <0.025). Alcohol consumption is a risky behavior that deserves to be recognized by the main actors about neurocognitive effects. Alcohol consumption prevention programs and cognitive diagnostic tools are appropriate strategies to reduce risk behaviors in mental health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".