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Record W4362473019 · doi:10.6004/jnccn.2022.7109

CLO23-025: Comparison of Outcomes Using NCCN Classification in Two Concurrent Phase III Trials in Intermediate and High Risk Prostate Cancer: Long-Term Data

2023· article· en· W4362473019 on OpenAlexaff
Abdenour Nabid, Nathalie Carrier, Éric Vigneault, André‐Guy Martin, Thu Van Nguyen, Jean-Paul Bahary, Peter Vavassis, Marc-André Brassard, Sylvie Vass, Boris Bahoric, Robert Archambault, F. Vincent, Rédouane Bettahar, Marie Duclos, Derek Wilke, Luís Souhami

Bibliographic record

VenueJournal of the National Comprehensive Cancer Network · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-QuébecCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanCentre Hospitalier de l’Université de MontréalHôpital Maisonneuve-RosemontNova Scotia Cancer CentreCentre hospitalier universitaire de QuébecMcGill University Health CentreCentre Intégré de Santé et de Services Sociaux du Bas-Saint-LaurentCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsMedicineProstate cancerTerm (time)OncologyCancerInternal medicineClinical trialProstate

Abstract

fetched live from OpenAlex

"CLO23-025: Comparison of Outcomes Using NCCN Classification in Two Concurrent Phase III Trials in Intermediate and High Risk Prostate Cancer: Long-Term Data" published on 31 Mar 2023 by National Comprehensive Cancer Network.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.025
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.320
GPT teacher head0.535
Teacher spread0.215 · 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 teacher head, 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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