Genetic polymorphisms in genes related to risk‐taking behaviours predicting body mass index trajectory among Mexican American adolescents
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
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.
Bibliographic record
Abstract
OBJECTIVES: Obesity is associated with multiple health problems and often originates in childhood. The purpose is to investigate the associations of genetic polymorphisms in genes related to risk-taking behaviours with body mass index (BMI) trajectory over adolescence among Mexican Americans. METHODS: This study included 1229 Mexican American adolescents who participated in a large population-based cohort study in Houston, Texas. BMI data were obtained at baseline and two follow-ups. The median follow-up time was 59 months. Participants were genotyped for 672 functional and tagging variants in genes involved in the dopamine, serotonin and cannabinoid pathways. RESULTS: After adjusting for multiple comparisons, three genetic variants, namely, rs933271 and rs4646310 in COMT gene, and rs9567733 in HTR2A gene were significantly associated with BMI growth over adolescence. Using those three variants, we created an allelic score, and the allelic score was associated with BMI growth over adolescence (P < 0.001). With the increase number of variant allele, the rate of BMI growth over adolescence was slower. Finally, we identified another two genetic variants, namely, rs17069005 in HTR2A gene and rs3776511 in SLC6A3A gene were associated with obesity at last follow-up. CONCLUSIONS: The results suggest that genetic variants in selected genes involved in dopamine and serotonin pathways have noticeable effects on BMI over adolescence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it