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Record W4225009152 · doi:10.1080/10903127.2022.2044417

Joint Statement on Lights & Siren Vehicle Operations on Emergency Medical Services Responses

2022· article· en· W4225009152 on OpenAlexaff
Douglas F. Kupas, Matt Zavadsky, Brooke Burton, Shawn Baird, Jeff Clawson, Chip Decker, Peter Dworsky, Bruce Evans, David Finger, Jeffrey M. Goodloe, Brian LaCroix, Gary Ludwig, Michael McEvoy, David K. Tan, Kyle L. Thornton, Kevin M. Smith, Bryan Wilson

Bibliographic record

VenuePrehospital Emergency Care · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicData Quality and Management
Canadian institutionsNiagara College
Fundersnot available
KeywordsSiren (mythology)MedicineEmergency medical servicesMedical emergencyStatement (logic)Joint (building)AeronauticsEngineeringLaw

Abstract

fetched live from OpenAlex

The National Association of EMS Physicians and the then National Association of State EMS Directors created a position statement on emergency medical vehicle use of lights and siren in 1994 (1). Th...

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)0.038
metaresearch head score (Gemma)0.079
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 score0.052
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.079
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.003
Science and technology studies0.0040.003
Scholarly communication0.0110.003
Open science0.0050.006
Research integrity0.0380.025
Insufficient payload (model declined to judge)0.0200.013

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 head0.118
GPT teacher head0.412
Teacher spread0.294 · 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".

Quick stats

Citations9
Published2022
Admission routes1
Has abstractno

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