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Record W3093954696 · doi:10.1136/bmjpo-2020-000840

Vaping-related injury and illness among Canadian children and adolescents: a one-time survey of paediatric providers

2020· article· en· W3093954696 on OpenAlex
Nicholas Chadi, Charlotte Moore Hepburn, Suzanne Beno, Sarah A. Richmond

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBMJ Paediatrics Open · 2020
Typearticle
Languageen
FieldMedicine
TopicRestraint-Related Deaths
Canadian institutionsPublic Health OntarioUniversity of TorontoHospital for Sick ChildrenCentre Hospitalier Universitaire Sainte-Justine
FundersSociété Canadienne de PédiatriePublic Health AgencyPublic Health Agency of Canada
KeywordsMedicineIntensive care unitEmergency medicinePediatricsMedical emergencyEnvironmental healthFamily medicineIntensive care medicine

Abstract

fetched live from OpenAlex

A one-time survey distributed to 2693 Canadian paediatricians enrolled in the Canadian Paediatric Surveillance Programme was conducted between October and December 2019. We identified a wide range of severe vaping-related injuries and illnesses among children ages 0-17 (n=88), which were associated with the routine use or malfunctioning of a vaping device or the ingestion of vaping substances. The most common clinical presentations were acute respiratory symptoms and nicotine toxicity and 15% (n=13) of injuries required intensive care unit admission. Our study highlights the urgent need for substantive policy measures to help protect youth against the risks associated with vaping products.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.271
Teacher spread0.252 · 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