Drs Sanchez-Gistau and Castro-Fornieles Reply
Bibliographic record
Abstract
Article AbstractBecause this piece does not have an abstract, we have provided for your benefit the first 3 sentences of the full text.To the Editor: We appreciate the interest of Dr Patil and colleagues in our study about predictors of suicide attempt in early-onset, first episode psychoses.Dr Patil and colleagues raise concerns about a number of methodological issues of the study. First, with regard to the suitability of the Positive and Negative Syndrome Scale (PANSS) in measuring psychotic symptoms in adolescents, many studies have used the PANSS for the assessment of psychotic symptoms in early-onset schizophrenia (see recent reviews by Schimmelmann et al and by Clemmensen et al).Second, the Children's Depression Rating Scale (CDRS), which is derived from the HDRS Hamilton Depression Rating Scale (HDRS),was developed to assess depressive symptoms in children aged 6 to 12 years.
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.023 | 0.029 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".