MétaCan
Menu
Back to cohort
Record W2464481495 · doi:10.1159/000468320

Use of Psychotropics in the World

2017· article· en· W2464481495 on OpenAlex
‌Barry Reisberg, Susan Simeon

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Pharmacopsychiatry · 2017
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineManiaPsychiatryChlorpromazineDepression (economics)Schizophrenia (object-oriented programming)Psychotropic drugImipramineLithium (medication)DiazepamDrugBipolar disorderAlternative medicinePharmacology

Abstract

fetched live from OpenAlex

A questionnaire regarding medication preferences for major categories of psychiatric disorders was sent to 1,059 psychiatric drug investigators in 53 countries. 264 questionnaires were returned, of which 165 were appropriate for this survey. A total of 87 different psychotropic drugs were selected. Chlorpromazine was the medication most frequently cited in the treatment of schizophrenia. Amitriptyline and imipramine together accounted for the vast majority of medication chosen for all varieties of depression. In the treatment of mania, chlorpromazine was chosen by almost one-third of our sample, lithium by only one-fifth. Chlordiazepoxide and diazepam were equally preferred in the treatment of alcoholism. Most psychiatrists preferred not to use any psychotropic medications consistently in treating patients with organic brain syndromes. The implications of this study are discussed and compared uith similar studies in more limited geographical regions and in children.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.090
GPT teacher head0.429
Teacher spread0.340 · 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