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Record W6964389340 · doi:10.25384/sage.14562416

sj-docx-2-hpp-10.1177_1524839921996350 – Supplemental material for Systematic Review of Arts-Based Interventions to Address Suicide Prevention and Survivorship in Australia, Canada, the United Kingdom, and the United States of America

2021· article· en· W6964389340 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionSurvivorship curveSuicide preventionPoison controlHealth promotionOccupational safety and healthInjury preventionPublic health

Abstract

fetched live from OpenAlex

Supplemental material, sj-docx-2-hpp-10.1177_1524839921996350 for Systematic Review of Arts-Based Interventions to Address Suicide Prevention and Survivorship in Australia, Canada, the United Kingdom, and the United States of America by Jill Sonke, Kelley Sams, Jane Morgan-Daniel, Andres Pumariega, Faryal Mallick, Virginia Pesata and Nicola Olsen in Health Promotion Practice

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)0.078
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: Systematic review · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.982
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.078
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0140.022
Science and technology studies0.0010.001
Scholarly communication0.0080.008
Open science0.0040.005
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.9350.357

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 head0.123
GPT teacher head0.366
Teacher spread0.243 · 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 designSystematic review
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
Published2021
Admission routes1
Has abstractyes

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