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Record W4376640530 · doi:10.1158/1078-0432.ccr-23-0652

An Attempt to Stretch the Benefit: Rechallenge with PARP Inhibitors in Ovarian Cancer

2023· editorial· en· W4376640530 on OpenAlexaff
Eduardo González-Ochoa, Amit M. Oza

Bibliographic record

VenueClinical Cancer Research · 2023
Typeeditorial
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsOlaparibOvarian cancerPoly ADP ribose polymeraseSynthetic lethalityPARP inhibitorMedicineHomologous recombinationBRCA mutationCancerCancer researchOncologyInternal medicineBiologyDNA repairGeneticsGenePolymerase

Abstract

fetched live from OpenAlex

PARP inhibitors exploit synthetic lethality in homologous recombination-deficient (HDR) cells and are standard-of-care treatment in newly diagnosed and relapsed epithelial ovarian cancer (EOC). A recent article demonstrated that a second course of olaparib can be safely administered to women with BRCA-mutated EOC. See related article by Morgan et al., p. 2602.

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)0.006
metaresearch head score (Gemma)0.013
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.012
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0030.001
Research integrity0.0120.027
Insufficient payload (model declined to judge)0.0050.005

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 head0.295
GPT teacher head0.591
Teacher spread0.296 · 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
GenreEditorial

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

Citations3
Published2023
Admission routes1
Has abstractyes

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