MétaCan
Menu
← Back to cohort
Record W4241340003 · doi:10.3410/f.735536620.793560172

Faculty Opinions recommendation of Sustained rescue of prefrontal circuit dysfunction by antidepressant-induced spine formation.

2019· dataset· en· W4241340003 on OpenAlexaff
Bryan Kolb

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2019
Typedataset
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of Lethbridge
FundersWeill Cornell Medical CollegeCore Research for Evolutional Science and TechnologyOne MindJapan Agency for Medical Research and DevelopmentNational Institute of General Medical SciencesNational Institute of Mental HealthWhitehall FoundationJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and TechnologyNational Institutes of HealthNational Science Foundation
KeywordsAntidepressantPsychologyNeurosciencePsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION:Depression is an episodic form of mental illness, yet the circuit-level mechanisms driving the induction, remission, and recurrence of depressive episodes over time are not well understood.Keta-mine relieves depressive symptoms rapidly, providing an opportunity to study the neuro-biological substrates of transitions from depression to remission and to test whether mechanisms that induce antidepressant effects acutely are distinct from those that sustain them.RATIONALE: Contrasting changes in dendritic spine density in prefrontal cortical pyramidal cells have been associated with the emergence of depression-related behaviors in chronic stress

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)0.001
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.999
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1070.072

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 head0.038
GPT teacher head0.345
Teacher spread0.307 · 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
DomainEvaluation
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature→Same topicTreatment of Major Depression→French-language works237,207→