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Record W2024892961 · doi:10.1016/j.eururo.2011.07.066

External Validation of Postoperative Nomograms for Prediction of All-Cause Mortality, Cancer-Specific Mortality, and Recurrence in Patients With Urothelial Carcinoma of the Bladder

2011· article· en· W2024892961 on OpenAlexaff
Philipp Nuhn, Matthias May, Maxine Sun, Hans‐Martin Fritsche, Sabine Brookman‐May, Alexander Büchner, Christian Bolenz, Rudolf Moritz, Edwin Herrmann, Maximilian Burger, Derya Tilki, Lutz Trojan, Paul Perrotte, Axel Haferkamp, Markus Hohenfellner, Wolf F. Wieland, Stefan Müller, Pierre I. Karakiewicz, Patrick J. Bastian

Bibliographic record

VenueEuropean Urology · 2011
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsNomogramMedicineBladder cancerReceiver operating characteristicUrologyCystectomyCohortArea under the curveRetrospective cohort studySurgeryCancerOncologyInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.047
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.084
GPT teacher head0.294
Teacher spread0.210 · 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 designObservational
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

Citations86
Published2011
Admission routes1
Has abstractno

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