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Record W7062234748

Spatial analysis of ischemic heart disease in Manitoba

2019· dissertation· en· W7062234748 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMspace (University of Manitoba) · 2019
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Power Generation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsCluster (spacecraft)PopulationDiseaseAutoregressive modelPoisson regressionEpidemiologyPoisson distributionSpatial epidemiologySpatial ecology
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Chronic diseases rarely follow uniform distributions throughout geographical space and so identifying regions that have frequent occurrences or elevated prevalences is important. The disease of interest for this research project was ischemic heart disease (IHD). Objectives: The purpose of this project was to use statistical tools to detect spatial and temporal patterns of IHD in Manitoba. The objectives were to: (1) detect geographic clusters of acute myocardial infarctions (AMI) within Manitoba; (2) assess whether IHD is related to the geographic distribution of some its well-known risk factors; and (3) what relationship IHD has to the temporal dimension throughout geographic space. Methods: The first objective was assessed using the flexible spatial scanner to detect clusters of AMIs. The second objective was assessed using spatial Poisson regression models that modelled the spatial covariance with conditional autoregressive structures. The third objective was assessed by extending the spatial model to the temporal dimension by modeling the temporal covariance with random-walk covariance structures. Space-time interaction effects were assessed to complete the evaluation of the third objective. Results: One primary and eight secondary disease clusters of AMIs were identified, where the primary cluster occurred in the central Manitoba region. Hypertension prevalence and indigenous population proportion significantly predicted IHD prevalence. When controlling for temporal autocorrelation, indigenous population proportion was no longer a significant predictor of IHD. The results were within error the same for males and females when stratifying by sex. Modelled IHD prevalence was found to be decreasing over time, but the majority of this occurred in the female sub-group. Counter to this finding, IHD prevalence in some regions substantially increased over the study period. Conclusions: This research identified AMI clusters as well as modelled the spatial and temporal variation in IHD within 96 regions in Manitoba over 23 years. It was found that there were significant associations between IHD and the two covariates of hypertension and indigenous population proportion. The most significant effect was the space-time interaction, suggesting that the temporal patterns in IHD prevalence vary significantly throughout space, with some regions having significantly increasing trends over time counter to the provincial average.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.195
Teacher spread0.188 · 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