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Record W4388500626 · doi:10.1111/his.15091

Head‐to‐head: how many categories for grading urothelial carcinoma?

2023· review· en· W4388500626 on OpenAlexaff
Murali Varma, Éva Compérat, Theodorus van der Kwast

Bibliographic record

VenueHistopathology · 2023
Typereview
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsGrading (engineering)Urothelial carcinomaMedicineCarcinomaUrothelial cancerBladder cancerOncologyPathologyRadiologyInternal medicineCancerBiology

Abstract

fetched live from OpenAlex

Tumour grade is a critical prognostic parameter for guiding the management of patients with non-muscle invasive bladder cancer. In 2004, the World Health Organisation (WHO) adopted a binary (low-grade/high-grade) grading system to replace the three-tier (grades 1-3) system used to grade urothelial carcinoma since 1973. However, there is significant global variation in the grading of urothelial carcinoma. Some pathology and clinical guidelines recommend reporting of the WHO 1973 and 2004 grades in parallel, while others require reporting only of the WHO 2004 grade. This variation in pathology practice is clinically significant, because the two grading systems are not readily translatable. Some experts have proposed novel systems for grading urothelial carcinoma that involve splitting of the WHO 1973 and 2004 grade categories. The arguments for and against splitting urothelial carcinomas into two-, three- and four-grade categories are independently discussed by the three authors.

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)0.010
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0040.004
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.004

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 head0.137
GPT teacher head0.399
Teacher spread0.262 · 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
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

Citations2
Published2023
Admission routes1
Has abstractyes

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