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Record W6888988456 · doi:10.25384/sage.12999280

Supplementary_File_1_-_list_of_BD_agents_from_search - A Systematic Review of Nutraceuticals for the Treatment of Bipolar Disorder: Une revue systématique des nutraceutiques pour le traitement du trouble bipolaire

2020· article· fr· W6888988456 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2020
Typearticle
Languagefr
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsClinical PracticeMEDLINEDiseaseMedical treatmentSystematic review

Abstract

fetched live from OpenAlex

Supplementary_File_1_-_list_of_BD_agents_from_search for A Systematic Review of Nutraceuticals for the Treatment of Bipolar Disorder: Une revue systématique des nutraceutiques pour le traitement du trouble bipolaire by Melanie M. Ashton, Bianca E. Kavanagh, Wolfgang Marx, Michael Berk, Jerome Sarris, Chee H. Ng, Malcolm Hopwood, Lana J. Williams and Olivia M. Dean in The Canadian Journal of Psychiatry

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)0.004
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.750
Threshold uncertainty score0.356

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.065
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0120.022
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.7500.065

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 head0.096
GPT teacher head0.363
Teacher spread0.267 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

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