MétaCan
Menu
Back to cohort
Record W2409496214 · doi:10.1097/pec.0000000000000705

Managing Children With Autism Spectrum Disorders in Emergency Departments

2016· article· en· W2409496214 on OpenAlexaff
Shafiqa Al Sharif, Savithiri Ratnapalan

Bibliographic record

VenuePediatric Emergency Care · 2016
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsAutismMedicineAutism spectrum disorderIncidence (geometry)Emergency departmentPsychiatryHealth careBroad spectrumPediatricsMedical emergencyFamily medicine

Abstract

fetched live from OpenAlex

Taking care of children with autism spectrum disorders is not uncommon in emergency departments as they visit hospital for acute medical and psychiatric conditions. The current prevalence and increasing incidence of autism spectrum disorders will increase the demand for hospital and outpatient services for these children, necessitating education of health care professionals and system adaptations. This paper describes a patient with autism spectrum disorder who had some challenging behavior in the emergency department when he presented with anaphylaxis and discusses management strategies that would help in caring for children with autism spectrum disorders.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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 teacher head, not a consensus.

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

Citations16
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePediatric Emergency CareSame topicAutism Spectrum Disorder ResearchFrench-language works237,207