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Record W2267070502 · doi:10.3402/ijch.v75.30059

Cancer incidence and mortality among the Métis population of Alberta, Canada

2016· article· en· W2267070502 on OpenAlexaffabout
Diana C. Sanchez‐Ramirez, Amy Colquhoun, Sara Lynn Parker, Jason R. Randall, Lawrence W. Svenson, Don Voaklander

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2016
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of ManitobaMétis National CouncilUniversity of CalgaryAlberta HealthUniversity of Alberta
Fundersnot available
KeywordsMedicineIncidence (geometry)Cancer registryPopulationLung cancerDemographyEpidemiologyCancerCancer incidenceMortality rateGerontologyEnvironmental healthSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer has been identified as a major cause of morbidity and mortality in Canada over the last decade. However, there is a paucity of information about cancer patterns in Aboriginal people, particularly for Métis. This study aims to explore cancer incidence and mortality burden among Métis and to compare disease estimates with non-Métis population. METHODS: This population-based descriptive epidemiological study used cancer incidence and mortality data from 2007 to 2012 obtained from Alberta Health Care Insurance Plan (AHCIP) - Central Stakeholder Registry - and Alberta Cancer Registry (ACR). To identify cancer cases in Métis, the ACR was linked with the Métis Nation of Alberta (MNA) Identification Registry. In Métis and non-Métis people, age-standardized cancer incidence and mortality rates were estimated and subsequently compared between both groups. RESULTS: A higher incidence of bronchus/lung cancer was found among Métis men compared with their non-Métis counterparts (RR=1.69, CI 1.28-2.09; p=0.01). No other statistically significant differences in cancer incidence or mortality were found between Métis and non-Métis people living in Alberta over the course of the 6 years studied. CONCLUSIONS: Overall incidence and mortality associated with cancer were not higher among Métis people compared with non-Métis people. However, special efforts should be considered to decrease the higher incidence of bronchus/lung cancer in Métis men. Further development and maintenance of new and existing institutional collaborations are necessary to continue cancer research and health status surveillance in Métis population.

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 score0.115
Threshold uncertainty score0.271

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 head0.038
GPT teacher head0.369
Teacher spread0.331 · 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

Citations16
Published2016
Admission routes2
Has abstractyes

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