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Record W4380538153 · doi:10.1186/s13053-023-00252-6

Genetic testing for hereditary breast cancer in Poland: 1998–2022

2023· letter· en· W4380538153 on OpenAlexaff
Jacek Gronwald, Cezary Cybulski, Tomasz Huzarski, Anna Jakubowska, Tadeusz Dębniak, Marcin Lener, Steven A. Narod, Jan Lubiński

Bibliographic record

VenueHereditary Cancer in Clinical Practice · 2023
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsPublic Health OntarioWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineGenetic testingBreast cancerOvarian cancerCancerMutationFamily historyGenetic counselingGynecologyOncologyHuman geneticsInternal medicineGeneticsGeneBiology

Abstract

fetched live from OpenAlex

BRCA1 and BRCA2 mutations contribute to both breast cancer and ovarian cancer worldwide. In Poland approximately 4% of patients with breast cancers and 10% of patients with ovarian cancer carry a mutation in BRCA1. The majority of mutations consist of three founder mutations. A rapid inexpensive test for these three mutations can be used to screen all Polish adults at a reasonable cost. In the region of Pomerania of North-western Poland nearly half a million tests have been performed, in large part through engaging family doctors and providing ready access to testing through the Pomeranian Medical University. The following commentary provides a history of genetic testing for cancer in Pomerania and the current approach to facilitating access to genetic testing at the Cancer Family Clinic for all adults living in the region.

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)0.007
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: none
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0190.010
Insufficient payload (model declined to judge)0.0020.001

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 head0.064
GPT teacher head0.405
Teacher spread0.341 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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