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Record W1987966855 · doi:10.1159/000117539

α-Methyldopa—Chlorpromazine Combination in Schizophrenic Patients

2008· article· en· W1987966855 on OpenAlexaff
Guy Chouinard, L Annable

Bibliographic record

VenueNeuropsychobiology · 2008
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsInstitut universitaire en santé mentale de MontréalInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsChlorpromazinePsychologySchizophrenia (object-oriented programming)PsychosisPsychiatryMedicineAnesthesiaNeurosciencePharmacology

Abstract

fetched live from OpenAlex

In a double-blind, controlled clinical study, lasting 8 weeks, 55 hospitalized schizophrenic patients were randomly assigned to one of the five drug treatments: 600 mg chlorpromazine/day, 300 mg chlorpromazine/day, 300 mg chlorpromazine--250 mg alpha-methyldopa/day, 300 mg chlorpromazine--500 mg alpha-methyldopa/day, 300 mg chlorpromazine--750 mg alpha-methyldopa/day. The results showed that all five treatments were significantly effective in treating schizophrenic behavior. The dose-response relationship for the different doses of alpha-methyldopa in combination with chlorpromazine, suggested an optimal response to 300 mg chlorpromazine--500 mg alpha-methyldopa.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.284
Teacher spread0.261 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
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

Citations7
Published2008
Admission routes1
Has abstractyes

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