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Record W6908009641 · doi:10.25384/sage.23910418

sj-docx-1-cjk-10.1177_20543581231190180 – Supplemental material for Reducing Dietary Acid With Fruit and Vegetables Versus Oral Alkali in People With Chronic Kidney Disease (ReDACKD): A Clinical Research Protocol

2023· article· en· W6908009641 on OpenAlexaffabout

Bibliographic record

VenueSage Journals Data · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsDalhousie UniversityUniversity of Manitoba
Fundersnot available
KeywordsKidney diseaseClinical researchDiseaseProtocol (science)Kidney

Abstract

fetched live from OpenAlex

Supplemental material, sj-docx-1-cjk-10.1177_20543581231190180 for Reducing Dietary Acid With Fruit and Vegetables Versus Oral Alkali in People With Chronic Kidney Disease (ReDACKD): A Clinical Research Protocol by Rebecca Mollard, Katrina Cachero, Bohdan Luhovyy, Heather Martin, Sharon Moisiuk, Sepideh Mahboobi, Robert Balshaw, David Collister, Leah Cahill, Karthik K. Tennankore, Navdeep Tangri and Dylan MacKay in Canadian Journal of Kidney Health and Disease

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.150
GPT teacher head0.450
Teacher spread0.300 · 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
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

Citations0
Published2023
Admission routes2
Has abstractyes

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