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Record W2064951735 · doi:10.2105/ajph.2012.300670

Shifts in Mortality During a Hot Weather Event in Vancouver, British Columbia: Rapid Assessment With Case-Only Analysis

2012· article· en· W2064951735 on OpenAlexafffundabout
Tom Kosatsky, Sarah B. Henderson, Sue Pollock

Bibliographic record

VenueAmerican Journal of Public Health · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsBC Centre for Disease Control
FundersBritish Columbia Centre for Disease Control
KeywordsConfidence intervalOdds ratioOddsDemographyMedicineApparent temperatureGerontologyGeographyLogistic regressionMeteorologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: We assessed shifts in patterns of mortality during a hot weather event in greater Vancouver, British Columbia. METHODS: We used a case-only analysis to compare characteristics of individuals who died during the hottest week of 2009 with those who died (1) during earlier summer weeks in 2009 and (2) during the same calendar weeks in the summers of 2001 through 2008. RESULTS: Compared with the 8 previous weeks of 2009, odds of mortality during the summer's hottest week were highest in the 65 to 74 years age category, compared with the 85 years and older category (odds ratio [OR] = 1.47; 95% confidence interval [CI] = 1.06, 2.03). The number of deaths at home increased over deaths in hospitals or institutions (OR = 1.43; 95% CI = 1.10, 1.86). Densely populated administrative health areas were more affected. CONCLUSIONS: A shift toward deaths at home suggests that in-home-based protective measures should be part of planning for hot weather events in greater Vancouver. Targeting should be considered for those aged 65 to 74 years. The case-only approach is quick and easy to apply and can provide useful information about localized, time-limited events.

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)0.004
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 score0.593
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.340
Teacher spread0.296 · 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

Citations72
Published2012
Admission routes3
Has abstractyes

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