Bibliographic record
Abstract
Canadian who were living in Toronto for the past fifteen years after migrating from their own countries and maintaining their own traditional food habits, were studied for their adiposity and body composition. Body composition was analyzed by bio-impedance method using bioelectrical body composition analyzer and BMI was calculated by standard method. Average age, height, weight, fat % and BMI for the males were 34.2 yr (± 12.3), 175.8 cm (± 8.2), 85.5 kg (± 17.5), 23.6 % (± 7.4) and 27.6 kg.m 2 (± 5.2) respectively whereas those for their female counterparts were 30.9 yr (± 11.3), 163.7 cm (± 6.5), 71.1 kg (± 17.1), 31.8 % (± 8.2) and 26.5 kg.m -2 (± 5.9) respectively. A wide range of Fat % were observed in both male and female Canadians which were 7.3% - 50.0% for male and 8.5 %-52.6% for female. Similar wide ranges were also observed in BMI where males had a range of 14.6 kg.m -2 - 48.5 kg.m -2 and female had 15.2 kg.m -2 and 50.2 kg.m -2 . In males, 66.12 % were in overweight category, out of which 38.74% were in pre-obese and 27.38% were in obese group. Similarly, in females, 52.72% were in overweight category, out of which 30.96% were in pre-obese category and 21.75% were in obese category. High adiposity was also observed both in males and females. The reason might be due to their life style and food habit.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".