Bibliographic record
Abstract
Obesity is a multifactorial and largely preventable condition resulting from complex interactions between different biological and environmental factors. In recent decades, the disease has reached epidemic proportions as over one-third of the global population today is either overweight or obese. Adolescence and young adulthood may be critical periods for obesity development as elevated BMI during these periods have been associated with chronic obesity later in life. As such, young adulthood may be considered a favorable period for effective obesity prevention. Interestingly, while education status is negatively correlated with BMI in the general population from high-income countries, young adults with higher education have been shown to be at greater risk for weight gain than those without a post-secondary education. The “Freshman 15” is a popular theory that suggests that undergraduate students gain 15 pounds during their first year in university. While previous studies have found this to be an exaggerated estimate, they have indicated that, on average, students still tend to gain around 3-5 pounds during this period. Given that young adults pursuing undergraduate studies represent an at-risk group for increased BMI and the development of obesity later in adulthood, the predictors of weight gain in this population must be explored for the development of effective prediction and prevention strategies. This thesis compiles a series of investigations focused on identifying the effect of certain demographic and environmental factors on change in obesity traits among first-year university students from Ontario, Canada. Our investigations confirm the trend of weight gain among students during the first year of university, and implicate ethnicity and type of living arrangement, but not sex, as potential predictors within this context. These results may help promote further research in this area, and ultimately help us have a better understanding of the risk factors that make students susceptible to weight gain during first of university.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".