Bibliographic record
Abstract
Objective: To consider why the burden of depression persists. Method: The epidemiology and disability associated with depression were reviewed to consider whether depression persists because: the causes are overwhelming, prevention is ineffective, the disease is difficult to detect or diagnose, the condition remits and recurs, treatments do not work, individuals do not seek treatment, or effective care is not provided when they do seek it. Results: The first 5 possibilities were not considered significant reasons for the persistence of the burden. Conclusion: The burden persists because individuals do not seek treatment for their depression when they relapse and effective proactive treatment is not always provided when they do seek it. Objectif: Examiner pourquoi le fardeau de la dépression persiste. Méthode: L'épidémiologie et l'incapacité associées à la dépression ont été examinées pour déterminer si la dépression persiste parce que: les causes sont accablantes, la prévention est inefficace, la maladie est difficile à détecter ou à diagnostiquer, l'affection entre en rémission et revient, les traitements ne fonctionnent pas, les personnes ne veulent pas de traitement, ou des soins efficaces ne sont pas dispensés quand elles en veulent. Résultats: Les 5 premières possibilités n'ont pas été considérées comme étant des raisons significatives de la persistance du fardeau. Conclusion: Le fardeau persiste parce que les personnes ne veulent pas de traitement pour leur dépression quand elles rechutent, et qu'un traitement proactif efficace n'est pas toujours dispensé quand elles en veulent.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".