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Record W1969784042 · doi:10.1097/aci.0b013e328353351f

Measures of forest fire smoke exposure and their associations with respiratory health outcomes

2012· article· en· W1969784042 on OpenAlexaff
Sarah B. Henderson, Fay H. Johnston

Bibliographic record

VenueCurrent Opinion in Allergy and Clinical Immunology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of British ColumbiaBC Centre for Disease Control
Fundersnot available
KeywordsMedicineAsthmaEnvironmental healthSmokeEmergency medicineOutpatient visitsSecondhand smokeHealth careInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Exposure to forest fire smoke is episodic, which makes its health effects challenging to study. We review the newest contributions to a growing literature on acute respiratory outcomes. RECENT FINDINGS: Smoke exposure was associated with increases in self-reported symptoms, medication use, outpatient physician visits, emergency room visits, hospital admissions, and mortality. The associations were strongest for the outcomes most specific to asthma. SUMMARY: Studies with varied approaches to exposure assessment and varied measures of respiratory outcomes were consistent among themselves, and consistent with most previous work.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.050
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.089
GPT teacher head0.354
Teacher spread0.265 · 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.

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

Citations83
Published2012
Admission routes1
Has abstractyes

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