MétaCan
Menu
Back to cohort
Record W4388662575 · doi:10.1200/jco.23.00339

Olaparib for the Treatment of Patients With Metastatic Castration-Resistant Prostate Cancer and Alterations in <i>BRCA1</i> and/or <i>BRCA2</i> in the PROfound Trial

2023· article· en· W4388662575 on OpenAlexaff
Joaquı́n Mateo, Johann S. de Bono, Karim Fizazi, Fred Saad, Neal D. Shore, Shahneen Sandhu, Kim N., Neeraj Agarwal, David Olmos, Antoine Thiery-Vuillemin, Mustafa Özgüroğlu, Niven Mehra, Nobuaki Matsubara, Jae Young Joung, Charles Padua, Ernesto Korbenfeld, Jinyu Kang, Helen Marshall, Zhongwu Lai, Alan Barnicle, Christian Poehlein, Natalia Lukashchuk, Maha Hussain

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsBC Cancer AgencyCentre Hospitalier de l’Université de Montréal
FundersMedical Research CouncilNational Institute for Health and Care ResearchAstraZeneca
KeywordsOlaparibMedicineProstate cancerOncologyInternal medicinePARP inhibitorCancerClinical trialProstateGynecologyPoly ADP ribose polymerase

Abstract

fetched live from OpenAlex

Olaparib improved PFS and OS across subgroups of BRCA1/2mut #prostatecancer patients in the PROFOUND phase III trial.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.200
GPT teacher head0.501
Teacher spread0.301 · 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 designRandomized trial
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

Citations91
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicPARP inhibition in cancer therapyFrench-language works237,207