The Significance of Dietary Macronutrients in \nDiagnosis of Food Addiction
Bibliographic record
Abstract
Within the Western society, and indeed across all areas of the world, obesity rates are rising at an unprecedented pace. In 2011, it was reported by the Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group that measures of body mass index (BMI) are increasing in men and women from various regions of the globe. According to Statistics Canada’s 2013 Health Profile, 52.3% of Canadians are overweight or obese. Obesity has many causes, including genetics, environment, endocrinology, behavior, and nutrition. It is well-documented that overeating and dietary patterns are closely linked to obesity, with different foods have differing impacts on weight. The increased availability of food, along with the transition from traditional foods (rich in nutrients and low in calories) to those rich in fat and sugar has been coined the “westernization” of diet and has been observed in populations across Canada
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".