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Record W4387297143 · doi:10.1158/1078-0432.ccr-23-2260

Deciphering the Pathways to PARP Sensitivity in Pancreatic Cancer

2023· article· en· W4387297143 on OpenAlexafffund
Erica S. Tsang, Steven Gallinger

Bibliographic record

VenueClinical Cancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsOntario Institute for Cancer ResearchPrincess Margaret Cancer Centre
FundersOntario Institute for Cancer Research
KeywordsPALB2OlaparibPancreatic cancerPARP inhibitorReversionMedicineCancerOncologyClinical trialPoly ADP ribose polymeraseDNA repairCancer researchBRCA mutationInternal medicineBioinformaticsMutationBiologyGeneticsGermline mutationDNABreast cancerPhenotypePolymerase

Abstract

fetched live from OpenAlex

A recent article analyzed paired cell-free DNA among patients with platinum-sensitive BRCA- or PALB2-mutated pancreatic cancer who received maintenance olaparib. Reversion mutations were linked with worse outcomes. These types of paired correlative studies are needed to improve our understanding of drug resistance and guide future clinical trials. See related article by Brown et al., p. 5207.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.496
GPT teacher head0.592
Teacher spread0.096 · 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 designBench or experimental
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 routes2
Has abstractyes

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