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Record W4225014396 · doi:10.1038/s41398-022-01932-y

Correction: Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles

2022· erratum· en· W4225014396 on OpenAlexaff
Sabina I. Franklyn, Jayme Stewart, Cécile Beaurepaire, Emily Thaw, Robyn J. McQuaid

Bibliographic record

VenueTranslational Psychiatry · 2022
Typeerratum
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsCarleton UniversityRoyal Ottawa Mental Health CentreUniversity of Ottawa
Fundersnot available
KeywordsDepressive symptomsSchizophrenia (object-oriented programming)MedicineClinical psychologyMEDLINEPsychiatryPsychologyCognitionBiology

Abstract

fetched live from OpenAlex

The production team removed necessary commas in the reporting of the degrees of freedom for each F-test, significantly changing the meaning of the sample size for each test. This was an error introduced by the publication team. We apologize for these errors. The original article has been corrected.

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)0.006
metaresearch head score (Gemma)0.110
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.067
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.110
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0030.003
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0100.015
Insufficient payload (model declined to judge)0.0670.040

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2022
Admission routes1
Has abstractno

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