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Record W4385351309 · doi:10.14740/wjnu443

Greens Mean Go: A Case Report Exploring a Vegetarian Diet in Chronic Kidney Disease

2023· article· en· W4385351309 on OpenAlexvenueno aff
Qwynton Johnson, Alexis Kirk, S. D. Sykes, Andrea Asiedu, Sundeep Shah

Bibliographic record

VenueWorld Journal of Nephrology and Urology · 2023
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineKidney diseaseDialysisRegimenRenal functionInternal medicineDiseaseKidneyIntensive care medicine

Abstract

fetched live from OpenAlex

An 81-year-old Caucasian male with stage 4 chronic kidney disease (CKD) successfully avoided dialysis through specific lifestyle modifications. By following a strict vegetarian diet, avoiding animal proteins entirely, and adhering to a medication regimen, there was an immediate improvement in his kidney function. Three years into his newly adopted lifestyle, he remains off dialysis. This case report discusses the complex relationship between diet and chronic kidney disease. World J Nephrol Urol. 2023;12(1):17-21 doi: https://doi.org/10.14740/wjnu443

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.004
Science and technology studies0.0050.002
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.034
GPT teacher head0.284
Teacher spread0.250 · 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 designCase report
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 routes1
Has abstractyes

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