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Record W1958421425 · doi:10.6004/jnccn.2015.0094

Follow-Up Management of Patients With Testicular Cancer: A Multidisciplinary Consensus-Based Approach

2015· review· en· W1958421425 on OpenAlexaboutno aff
Clair J. Beard, Shilpa Gupta, Robert J. Motzer, Elizabeth O’Donnell, Elizabeth R. Plimack, Kim Margolin, Charles J. Ryan, Joel Sheinfeld, Darren R. Feldman

Bibliographic record

VenueJournal of the National Comprehensive Cancer Network · 2015
Typereview
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTesticular cancerMultidisciplinary approachCancerFamily medicineGynecologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Testicular cancer is the most common cancer in men aged 15 to 40 years in the United States, Canada, and many European countries. Given the excellent prognosis of most men with testicular cancer, updates in care after treatment have become very important. This article provides a review of the available evidence, integrated with expert medical judgment, in the area of testicular cancer follow-up.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.083
GPT teacher head0.368
Teacher spread0.286 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

Explore more

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