Diabète insulino-dépendant et comportement alimentaire chez l’adolescente
Bibliographic record
Abstract
Les troubles du comportement alimentaire seraient deux fois plus frequents chez les jeunes femmes et jeunes filles diabetiques que chez celles qui n'ont pas de diabete. C'est du moins ce qu'a revele une etude cas-temoin effectuee au Canada par Jones et al. [1]. C'est le fait que l'instauration d'une insulinotherapie entraine souvent une prise de poids qui leur a suggere cette etude. De fait, ils ont observe des anomalies franches du comportement alimentaire chez 10 % de 356 adolescentes diabetiques versus 4 % de 1098 adolescentes temoins. On retrouvait egalement des problemes plus mineurs chez 14 % des jeunes diabetiques versus \r8 % des temoins. Un sous-dosage de \rl'insuline est une facon frequente chez ces jeunes filles de perdre du poids. Les jeunes diabetiques ayant des troubles du comportement alimentaire ont une HbA1c plus elevee que celles qui n'en ont pas (9,4 vs 8,6 %). Ainsi, les troubles du comportement alimentaire posent-ils un probleme particulier lorsqu'ils surviennent chez la jeune diabetique car ils s'associent a un mauvais controle metabolique et a un risque de retinopathie multiplie par trois [2].1. Jones J.M. et al. 2000. Eating disorders in adolescent females with and without type 1 diabetes : cross sectional study. BMJ 320 : 1563-1566.2. Rydall A.C., et al. 1997. Disordered eating behavior and microvascular complications in young women with insulin-dependant diabetes mellitus. N Engl J Med 336 : 1849-1854.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".