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Record W4393374552 · doi:10.1681/asn.0000000000000332

Secular Trends in Incidence of Treated Kidney Failure in the United States

2024· editorial· en· W4393374552 on OpenAlexaffabout
Mallory L. Downie, Bethany J. Foster

Bibliographic record

VenueJournal of the American Society of Nephrology · 2024
Typeeditorial
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsMcGill UniversityMcGill University Health CentreMontreal Children's Hospital
Fundersnot available
KeywordsSecular variationIncidence (geometry)MedicineDemographyInternal medicineMathematicsSociology

Abstract

fetched live from OpenAlex

1Division of Nephrology, Department of Pediatrics, Montreal Children's Hospital, McGill University Health Centre, Montreal, Quebec, Canada 2Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada 3Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada Correspondence: Dr. Bethany J. Foster, email: [email protected] See related article, "Age- and Race-Specific Changes in ESKD Incidence over Four Decades," on pages 456–465.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.000
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.002

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 head0.284
Teacher spread0.276 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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