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Record W4404526746 · doi:10.1148/radiol.241624

Increased Emergency Department Medical Imaging: Association with Short-Term Exposures to Ambient Heat and Particulate Air Pollution

2024· article· en· W4404526746 on OpenAlexafffund
Kate Hanneman, Omar Taboun, Anish Kirpalani, Birgit Ertl‐Wagner, Julien Aguet, Scott Delaney, Rachel C. Nethery, Joseph Choi, Hayley Panet, M. J. Brown, Heidi Schmidt, Ania Z. Kielar, Michael N. Patlas

Bibliographic record

VenueRadiology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity Health NetworkWestern University
FundersUniversity of TorontoRadiological Society of North America
KeywordsMedicineParticulatesAir pollutionEmergency departmentParticulate pollutionTerm (time)Environmental healthMedical emergencyEmergency medicine

Abstract

fetched live from OpenAlex

In an analysis of data collected over a 10-year period from four emergency departments, short-term exposures to ambient heat and particulate air pollution were associated with increased utilization of radiography and CT but not US or MRI.

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 categoriesInsufficient 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 score0.031
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.295
Teacher spread0.277 · 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

Citations26
Published2024
Admission routes2
Has abstractyes

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