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Record W2890786570 · doi:10.14740/wjon1144w

DNA Damage Repair (DDR) Mutations and the Utility of High-Risk Genetics Clinics in Metastatic Castration-Refractory Prostate Cancer (mCRPC)

2018· article· en· W2890786570 on OpenAlexvenueno aff
Nityam Rathi, Neysi Anderson, Samantha Greenberg, Jennie Vagher, Neeraj Agarwal, Andrew W. Hahn

Bibliographic record

VenueWorld Journal of Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsGermlineProstate cancerMedicineDNA repairGenetic testingGermline mutationSomatic cellOncologyCancerInternal medicineGeneCancer researchGeneticsMutationBiology

Abstract

fetched live from OpenAlex

Germline pathogenic variants (PVs) in DNA-repair genes have garnered increasing attention in metastatic prostate cancer, and more patients are having somatic and germline DNA testing performed. Interpretation of germline DNA testing is a novel challenge for many clinicians, and the results of germline DNA-repair gene testing have significant implications for men with advanced prostate cancer and their children and siblings. Here, we report the case of a man with metastatic castration-refractory prostate cancer and a pathogenic, germline BRCA2 variant. We discuss the significance of his referral to a high-risk genetics clinic and the unique targeted therapy that he responded to. World J Oncol. 2018;9(4):119-122 doi: https://doi.org/10.14740/wjon1144w

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.048
GPT teacher head0.402
Teacher spread0.354 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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