MétaCan
Menu
Back to cohort
Record W2961332087 · doi:10.1093/pch/pxz087

Paediatric hyperthermia-related deaths while entrapped and unattended inside vehicles: The Canadian experience and anticipatory guidance for prevention

2019· article· en· W2961332087 on OpenAlexaffabout
Karen Ho, Ripudaman Minhas, Elizabeth Young, Michael Sgro, Joelene Huber

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsHospital for Sick ChildrenSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsForgettingDistractionMedicineMedical emergencyGovernment (linguistics)Incidence (geometry)PsychologyPediatrics

Abstract

fetched live from OpenAlex

An average of 37 children die of hyperthermia inside parked vehicles annually in the USA. The majority of cases are due to a caregiver forgetting them (~55%), while ~13% are due to intentionally leaving children unattended and ~28% occur when children climb into unlocked vehicles. The cause of four per cent is unknown. There are no published data on incidence in Canada. Through information provided from provincial and territorial coroner's offices, Canadian government agencies and media reports, six cases of vehicular hyperthermia deaths were confirmed since 2013. Three were attributed to children left unintentionally in vehicles; one occurred after a child climbed into an unlocked vehicle and two cases are undetermined. Attention or memory lapses are hypothesized to occur due to distraction, stress, fatigue, or routine changes. Educating caregivers about the dangers of leaving children in vehicles and providing preventative strategies through anticipatory guidance may reduce these tragedies (see graphic abstract).

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.284
Teacher spread0.268 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicCardiac Arrest and ResuscitationFrench-language works237,207