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Record W2131640252 · doi:10.1177/0009922814540983

Autism in the Emergency Department

2014· article· en· W2131640252 on OpenAlexaffabout
Justine Cohen-Silver, Barbara Muskat, Savithiri Ratnapalan

Bibliographic record

VenueClinical Pediatrics · 2014
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsPublic Health OntarioUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsMedicineEmergency departmentTriageAutismPediatricsRetrospective cohort studyEmergency medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: This is a retrospective chart review of autistic patients presenting to the emergency department (ED) in a tertiary care pediatric center during the year 2011. RESULTS: There were 160 ED visits by 130 patients, 25% of visits were repeated, and 20% were admitted to the hospital. There were 126 (79%) male and 34 (21%) female patients mean age of 12 years, 79% had comorbid health conditions. Forty percent were CTAS 2 (Canadian Triage Acuity Score) acuity, 42% of visits were CTAS 3 acuity, and 7% rated their pain as "severe." Visits were for behavior (10%), neurological concern (13%), 3% dental related, and the remainder were for gastrointestinal infections and other complaints. Average length of stay was 6 hours 21 minutes, with 2-hour wait to start assessment with physician. CONCLUSIONS: Autism is a prevalent diagnosis and patients with autism are accessing the ED. We hope to use these demographic findings to better serve these patients and their families.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.092
GPT teacher head0.406
Teacher spread0.314 · 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

Citations27
Published2014
Admission routes2
Has abstractyes

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