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Record W6888961783 · doi:10.25384/sage.22097737.v1

sj-docx-1-cpa-10.1177_07067437231156000 - Supplemental material for Changes in mortality for the general population and individuals with pre-pandemic acute care for alcohol or opioids during the COVID-19 pandemic in Ontario, Canada

2023· article· en· W6888961783 on OpenAlexaffabout

Bibliographic record

VenueFigshare · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsInstitute for Clinical Evaluative SciencesOttawa HospitalBruyèreUniversity of Ottawa
Fundersnot available
KeywordsPandemicPopulationAcute careCoronavirus disease 2019 (COVID-19)AlcoholPrimary care

Abstract

fetched live from OpenAlex

Supplemental material, sj-docx-1-cpa-10.1177_07067437231156000 for Changes in mortality for the general population and individuals with pre-pandemic acute care for alcohol or opioids during the COVID-19 pandemic in Ontario, Canada by Daniel Thomas Myran, Erik Loewen Friesen, Michael Pugliese, Christina Milani and Peter Tanuseputro 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)0.001
metaresearch head score (Gemma)0.019
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: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.926
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.019
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.011
Science and technology studies0.0040.001
Scholarly communication0.0050.003
Open science0.0040.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.9260.568

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 head0.137
GPT teacher head0.419
Teacher spread0.282 · 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 designObservational
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
Published2023
Admission routes2
Has abstractyes

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