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Record W4200002077 · doi:10.18192/uojm.v11is4.6151

Department of Psychiatry Research Day: Conference Proceedings

2021· article· en· W4200002077 on OpenAlexvenueaboutno aff
Zacharie Saint-Georges, Bryce J. M. Bogie

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)Mental healthLibrary scienceMedical educationDiversity (politics)Event (particle physics)PsychologyMedicinePolitical sciencePsychiatryComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

UOJM is pleased to have collaborated with the Department of Psychiatry Research Day committee to put together this special issue. The University of Ottawa Department of Psychiatry virtually hosted its annual Research Day on November 17, 2021. This year’s theme was Climate Change and Mental Health. The online event welcomed 168 registered individuals. The abstracts found in these conference proceedings highlight the quality and diversity of ongoing research within the Department of Psychiatry. We’d like to thank all members of the planning committees, the UOJM team, and all students involved for their hard work in contributing to and finalizing this special issue.

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)0.014
metaresearch head score (Gemma)0.035
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 score0.294
Threshold uncertainty score0.984

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0090.001
Scholarly communication0.0130.004
Open science0.0040.009
Research integrity0.0090.016
Insufficient payload (model declined to judge)0.2940.169

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 head0.035
GPT teacher head0.289
Teacher spread0.255 · 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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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