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Record W4312784136 · doi:10.48083/gbma2534

A Systematic Review of Plant-Based Diets and Bladder Cancer: A Call for Further Research

2022· review· en· W4312784136 on OpenAlexvenueno aff
Jacob Taylor, Natasha Gupta, Jaime Blanck, Stacy Loeb

Bibliographic record

VenueSociété Internationale d’Urologie Journal · 2022
Typereview
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
FundersProstate Cancer Foundation
KeywordsBladder cancerMedicineCancerSystematic reviewOncologyInternal medicineMEDLINEBiology

Abstract

fetched live from OpenAlex

The relationship between plant-based dietary patterns and bladder cancer has not been extensively studied. Our objective was to perform a systematic review of the relationship between plant-based diets and bladder cancer risk and/or outcomes. We searched the literature for all relevant papers published before October 2020 was conducted. Of 74 identified records, only 2 references were included in the final qualitative analysis. These publications found that vegetarian diets are associated with a lower risk of bladder cancer diagnosis. We did not identify any studies investigating the impact of plant-based dietary patterns on outcomes for individuals diagnosed with bladder cancer, which represents an important area for further study.

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)0.020
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.075
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0090.012
Science and technology studies0.0010.001
Scholarly communication0.0040.006
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.217
GPT teacher head0.484
Teacher spread0.267 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2022
Admission routes1
Has abstractyes

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