MétaCan
Menu
Back to cohort
Record W4408821220 · doi:10.29173/cjen510

Special Issue of CJEN – The importance of harm reduction in emergency nursing practice

2025· article· en· W4408821220 on OpenAlexaffvenueabout
Heather McLellan, Dawn Peta, Gabriela Peguero-Rodriguez, Kar Lin Su, Jeanesse Bourgeois, Alexandra Lapierre, Michelle Lalonde, Matthew J. Douma, Christopher Picard

Bibliographic record

VenueCanadian Journal of Emergency Nursing · 2025
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsMount Royal University
Fundersnot available
KeywordsHarm reductionHarmNursingEmergency nursingReduction (mathematics)MedicineMedical emergencyPsychologyEmergency departmentSocial psychologyPublic health

Abstract

fetched live from OpenAlex

Special Issue of CJEN – The importance of harm reduction in emergency nursing practice / Numéro spécial du CJEN - L’importance de la réduction des méfaits dans la pratique des soins infirmiers d’urgence. Un article de la revue Canadian Journal of Emergency Nursing / Journal canadien des infirmières d’urgence (Harm Reduction Special Edition) diffusée par la plateforme Érudit.

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)0.005
metaresearch head score (Gemma)0.018
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.047
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0070.005
Open science0.0020.003
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0470.011

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 head0.040
GPT teacher head0.378
Teacher spread0.338 · 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
GenreEditorial

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
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Emergency NursingSame topicSuicide and Self-Harm StudiesFrench-language works237,207