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Record W6926623905 · doi:10.25384/sage.21951237

sj-docx-1-cjk-10.1177_20543581221150676 – Supplemental material for Development and Validation of Patient Education Tools for Deprescribing in Patients on Hemodialysis

2023· article· en· W6926623905 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2023
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsnot available
Fundersnot available
KeywordsDeprescribingHemodialysisHome hemodialysisKidney diseasePatient educationPatient assessmentDisease

Abstract

fetched live from OpenAlex

Supplemental material, sj-docx-1-cjk-10.1177_20543581221150676 for Development and Validation of Patient Education Tools for Deprescribing in Patients on Hemodialysis by Thomas Hyunwoo Cho, Patrick C. K. Ng, Melissa J. Lefebvre, Arlene Desjarlais, Dennis McCann, Blair Waldvogel, Marcello Tonelli, Amit X. Garg, JoAnne Wilson, Monica Beaulieu, Judith Marin, Cali Orsulak, Melanie Talson, Monica Sharma, Jordanne Feldberg, Clara Bohm and Marisa Battistella 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 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)0.004
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.915
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.9150.629

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 head0.091
GPT teacher head0.352
Teacher spread0.261 · 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.

Study designObservational
Domainnot available
GenreDataset

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 routes1
Has abstractyes

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