MétaCan
Menu
Back to cohort
Record W3211935010 · doi:10.1038/s41537-021-00183-y

Reply to: “Historical pursuits of the language pathway hypothesis of schizophrenia”

2021· letter· en· W3211935010 on OpenAlexaff
Lena Palaniyappan, Jingnan Du, Jie Zhang, Jianfeng Feng

Bibliographic record

VenueSchizophrenia · 2021
Typeletter
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsLawson Health Research InstituteWestern University
FundersNational Natural Science Foundation of China
KeywordsSchizophrenia (object-oriented programming)PsychologyLinguisticsPhilosophyPsychiatry

Abstract

fetched live from OpenAlex

We appreciate the comments by Dr. DeLisi 1 regarding our study investigating the genetic determinants of language-network dysconnectivity in early-stage schizophrenia 2 . In her comments, Dr. DeLisi highlights the missing historical context of the focus of our study and the lack of evidence linking our choice of language-related genes to the elevated genetic risk for schizophrenia. We concur with both of her observations and discuss how we can make further progress from the matters arising in this field of inquiry.

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)0.005
metaresearch head score (Gemma)0.034
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.085
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0070.005
Scholarly communication0.0050.005
Open science0.0030.003
Research integrity0.0850.064
Insufficient payload (model declined to judge)0.0070.005

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 head0.028
GPT teacher head0.262
Teacher spread0.234 · 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
GenreCommentary

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

Citations5
Published2021
Admission routes1
Has abstractno

Explore more

Same venueSchizophreniaSame topicSchizophrenia research and treatmentFrench-language works237,207