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Record W3198793789 · doi:10.1016/s2542-5196(21)00200-x

Mortality risk attributable to wildfire-related PM2·5 pollution: a global time series study in 749 locations

2021· review· en· W3198793789 on OpenAlex

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.

Bibliographic record

VenueThe Lancet Planetary Health · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsHealth CanadaUniversity of OttawaOttawa Public Health
FundersNational Institute of Environmental Health SciencesNational Key Research and Development Program of ChinaNational Health and Medical Research CouncilMedical Research CouncilMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaMinistry of Science and Technology, TaiwanNational Natural Science Foundation of ChinaFundação para a Ciência e a TecnologiaNatural Environment Research CouncilScience and Technology Commission of Shanghai MunicipalityGrantová Agentura České RepublikyAustralian Research CouncilSight Research UK
KeywordsPoisson regressionRelative riskMedicineEnvironmental healthDemographyPopulationAir pollutionMortality rateConfidence intervalSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: and mortality across various regions of the world. METHODS: exposure was calculated. FINDINGS: exposure during the study period. INTERPRETATION: was associated with increased risk of mortality. Urgent action is needed to reduce health risks from the increasing wildfires. FUNDING: Australian Research Council, Australian National Health & Medical Research Council.

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)0.004
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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.114
GPT teacher head0.399
Teacher spread0.285 · 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