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Record W2461867928 · doi:10.1017/s1121189x00002281

Do findings from new trials for schizophrenia fit with existing evidence: not duped … just beguiled?

2007· article· en· W2461867928 on OpenAlexfundno aff
Clive E Adams, Mahesh Jayaram

Bibliographic record

VenueEpidemiologia e Psichiatria Sociale · 2007
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsEnthusiasmSchizophrenia (object-oriented programming)PsychiatryChlorpromazinePsychologyPsychotherapistMedicinePharmacologySocial psychology

Abstract

fetched live from OpenAlex

No treatment has caused a greater revolution in the treatment of people with schizophrenia than chlorpromazine. The new generation of drugs has been embraced by psychiatry with an enthusiasm fostered by the unmet needs of both patients and industry. Recent, independently funded trials have highlighted already existing data illustrating how the new antipsychotics drugs are an additional advance but not a revolution. In this story there are lessons for psychiatry--to opt for science rather than seduction.

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 imitation

Not 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.

metaresearch head score (Codex)0.311
metaresearch head score (Gemma)0.602
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.689
Threshold uncertainty score0.850

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3110.602
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0090.010
Bibliometrics0.0050.006
Science and technology studies0.0020.012
Scholarly communication0.0130.036
Open science0.0080.006
Research integrity0.0140.021
Insufficient payload (model declined to judge)0.0120.004

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.

Opus teacher head0.380
GPT teacher head0.459
Teacher spread0.080 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
GenreEmpirical

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".

Quick stats

Citations9
Published2007
Admission routes1
Has abstractyes

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