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Record W2019465545 · doi:10.1017/s095026880600690x

An exploratory spatial analysis of pneumonia and influenza hospitalizations in Ontario by age and gender

2006· article· en· W2019465545 on OpenAlex
Eric Crighton, Sol Elliott, Rahim Moineddin, Pavlos Kanaroglou, Ross Upshur

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEpidemiology and Infection · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of TorontoMcMaster UniversityUniversity of Ottawa
Fundersnot available
KeywordsDemographyPublic healthPneumoniaGeographyMedicinePopulationEnvironmental healthGerontologyNursing

Abstract

fetched live from OpenAlex

Pneumonia and influenza represent a significant public health burden in Canada and abroad. Knowledge of how this burden varies geographically provides clues to understanding the determinants of these illnesses, and insight into the effective management of health-care resources. We conducted a retrospective, population-based, ecological-level study to assess age- and gender-specific spatial patterns of pneumonia and influenza hospitalizations in the province of Ontario, Canada from 1992 to 2001. Results revealed marked variability in hospitalization rates by age, as well as clear and statistically significant patterns of high rates in northern rural counties and low rates in southern urban counties. A moderate yet significant level of positive spatial autocorrelation (Moran's I=0.21, P<0.05) was found in the global data, with significant, age-specific clusters of high values or 'hot spots' identified in several northern counties. Findings illustrate the need for geographically focused prevention strategies, and resource and service allocation policies informed by regional and population-specific demands.

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)0.001
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 score0.216
Threshold uncertainty score0.296

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 head0.054
GPT teacher head0.362
Teacher spread0.308 · 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