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Record W4391179909 · doi:10.1016/j.ekir.2024.01.038

Barriers to Optimal Kidney Health Among Indigenous Peoples

2024· editorial· en· W4391179909 on OpenAlexaff
Swasti Chaturvedi, María Eugenia Bianchi, Aminu K. Bello, Harley Crowshoe, Jaquelyne T. Hughes

Bibliographic record

VenueKidney International Reports · 2024
Typeeditorial
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsAlberta Health ServicesUniversity of Alberta
Fundersnot available
KeywordsIndigenousColonialismMedicineThe arcticArcticIndigenous cultureSocioeconomicsEconomic growthEthnologyGeographyDevelopment economicsHistorySociologyArchaeologyEcologyOceanography

Abstract

fetched live from OpenAlex

Indigenous communities, peoples and nations are groups of people in a particular country or region who maintain a historical continuity with their culture, and traditional ways of life that predated pre-colonial invasions on their territories, with a determination to preserve and transmit such cultural norms for future generations. The United Nations estimated that over 476 million people identify as Indigenous, spread across 90 countries from the Arctic to the South Pacific accounting for nearly 6.2% of the total global population1.

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)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.300
Teacher spread0.294 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations5
Published2024
Admission routes1
Has abstractyes

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