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Comparing haloperidol with clozapine as treatments for schizophrenia

2024· article· en· W4401035913 on OpenAlexaff
Bingzhi Liao

Bibliographic record

VenueTheoretical and Natural Science · 2024
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsClozapineSchizophrenia (object-oriented programming)HaloperidolPsychosisPsychiatryPsychologyAntipsychoticPopulationDopamine receptor D2DopamineExtrapyramidal symptomsMedicinePharmacologyNeuroscience

Abstract

fetched live from OpenAlex

Schizophrenia affects about 1% of the total population. It is a complex psychological disorder that may be caused by the interaction between genetic and environmental factors. Studies have identified some candidate genes that may contribute to the cause of the disorder. However, most genetics finding in schizophrenia have not been implicated in clinical use. Antipsychotics are drugs commonly used to treat psychosis, such as schizophrenia. First-generation antipsychotics, or typical antipsychotics (e.g. haloperidol), were the first type of medicine for psychosis that was developed. They mainly target dopamine D2 receptors in the basal ganglia and possibly the mesolimbic pathway as antagonists. Second-generation antipsychotics, or atypical antipsychotics, including clozapine, were developed after typical antipsychotics. They have multiple targets and cause less extrapyramidal side effects. Since atypical antipsychotics target multiple receptors, the complexity of these drugs is extremely high, and we now do not have a solid understanding of their mechanism of action.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.013
GPT teacher head0.313
Teacher spread0.300 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations0
Published2024
Admission routes1
Has abstractyes

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