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Record W2128523102 · doi:10.4306/pi.2008.5.4.203

Peripheral Amino Acid Levels in Schizophrenia and Antipsychotic Treatment

2008· article· en· W2128523102 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePsychiatry Investigation · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmino Acid Enzymes and Metabolism
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchNational Alliance for Research on Schizophrenia and Depression
KeywordsSchizophrenia (object-oriented programming)BiomarkerAntipsychoticAmino acidHomocysteineMedicinePsychiatryHaloperidolPsychosisBioinformaticsInternal medicinePsychologyBiologyBiochemistryDopamine

Abstract

fetched live from OpenAlex

Abnormal levels of amino acids have been reported in patients with schizophrenia and have also been investigated as a biomarker to monitor antipsychotic treatment, however results have been inconsistent. The purpose of the present review is to summarize the evidence in the literature of whether amino acid levels can be a biomarker and predict the treatment outcome in schizophrenia. The current review does not support amino acid concentration as a useful biomarker for monitoring antipsychotic response in patients with schizophrenia, although there is evidence that high levels of serum homocysteine and glutamate might be considered as a trait marker for schizophrenia. This review has also highlighted a considerable dearth of studies, specifically of studies evaluating antipsychotic side-effects.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.530

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 head0.021
GPT teacher head0.244
Teacher spread0.222 · 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