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Record W3211196936 · doi:10.1503/cmaj.80232

Gerald Caplan, then and now: public mental health applications to the current psychological challenges of the pandemic

2021· letter· en· W3211196936 on OpenAlexaffvenue
Normand Carrey

Bibliographic record

VenueCanadian Medical Association Journal · 2021
Typeletter
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsPandemicMental healthPublic healthExacerbationPopulationCoronavirus disease 2019 (COVID-19)PsychiatryMedicinePsychologyEnvironmental healthNursingDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Mental health providers are struggling to meet the “surge on surge” pandemic demands for services, especially for the pediatric population. Mental health reactions to the pandemic range from adjustment reactions to its impact on the individual, or his or her social network, to exacerbation of

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)0.024
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 score0.049
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.005
Scholarly communication0.0050.008
Open science0.0020.003
Research integrity0.0490.059
Insufficient payload (model declined to judge)0.0120.007

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 head0.097
GPT teacher head0.404
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.

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

Citations3
Published2021
Admission routes2
Has abstractyes

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