Bibliographic record
Abstract
OBJECTIVE: To provide a context for classification in child psychiatry over last 45 years including debate over different approaches. METHOD: The context for classification of child psychiatric disorders has changed drastically since the introduction of categorical classification and the multi-axial formulation in the Diagnostic and Statistical Manual (DSM) and the International Classification of Disease (ICD). The authors review some historical factors including the shift in psychiatry to a universal classification system spanning the lifespan. RESULTS: The adaptation of categorical and universal diagnosis has resulted in a series of child-adult lifespan continuities and discontinuities about how problems are conceptualized within the categorical, multi-axial system. CONCLUSION: There is need for a more flexible classification system to incorporate emerging data from longitudinal and gene-environment (GxE) interaction studies within the framework of attachment, developmental and systems theory.
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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 | 0.022 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.038 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 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".