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Record W4289979372 · doi:10.47363/amr/2021(8)209

Characteristics of End-Stage Kidney Disease in a Cohort of Indigenous and Non-Indigenous Adults in Northwestern Ontario, Canada

2021· article· en· W4289979372 on OpenAlexafffundabout
Victoria Domonkos

Bibliographic record

VenueApplied Medical Research · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsNOSM UniversityLakehead UniversityUniversity of Ottawa
FundersNorthern Ontario Academic Medicine AssociationPfizer
KeywordsIndigenousKidney diseaseMedicinePopulationDialysisDiseaseCohortInternal medicineEnvironmental healthBiology

Abstract

fetched live from OpenAlex

Background: In Canada, the prevalence of chronic kidney disease is two-fold higher among Indigenous than non-Indigenous people. Direct comparisons of clinical characteristics between Indigenous and nonIndigenous end-stage kidney disease (ESKD) patients have not been previously conducted. We compared demographic and clinical characteristics of Indigenous and non-Indigenous adults with ESKD receiving dialysis at the primary hospital serving a region with 20% Indigenous population. Methods: During 4 years, 186 adults with ESKD were recruited for a clinical trial to analyze the response to pneumococcal immunization. Demographic and clinical data, including age, sex, residency, dialysis characteristics, etiology for chronic kidney disease, comorbidities, history of infections and prior pneumococcal immunization were compared between 91 Indigenous and 94 non-Indigenous individuals.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.254
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2021
Admission routes3
Has abstractyes

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