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Record W2058841252 · doi:10.1309/ajcpprzlg9kt9axl

Accuracy of Urine Cytology and the Significance of an Atypical Category

2009· article· en· W2058841252 on OpenAlex
Fadi Brimo, Robin T. Vollmer, Bruce W. Case, Armen Aprikian, Wassim Kassouf, Manon Auger

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2009
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsCytologyBiopsyMedicinePathologyClinical significance

Abstract

fetched live from OpenAlex

The "atypical urothelial cell" cytologic category is nonstandardized. We subclassify atypical cases to "atypical, favor a reactive process" or "atypical, unclear if reactive or neoplastic." We evaluated the predictive significance of atypical cases by looking at their histologic follow-up. Among the 1,114 patients and 3,261 specimens included, 282 specimens had histologic follow-up. An atypical diagnosis did not carry a significant increased risk of urothelial neoplasia compared with the benign category. Although an "atypical unclear" diagnosis carried a higher rate of detection of high-grade cancer on follow-up biopsy in comparison with "atypical reactive" or "negative" diagnoses (26/58 [45%] vs 15/52 [29%] and 16/103 [15.5%], respectively), this difference was not statistically significant. These results suggest that dividing atypical cases into 2 categories based on the level of cytologic suspicion of cancer does not add clinically relevant information within the atypical category. They also raise the question of the significance of the atypical category altogether.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.401
Teacher spread0.364 · 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