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Record W7097378712

BMC Medical Genetics BioMed Central Research article Founder mutations in BRCA1/2 are not frequent in Canadian Ashkenazi Jewish men with prostate cancer

2003· article· en· W7097378712 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsProstate cancerEpidemiologyMutationPopulationGermline mutationGermlineFounder effectProstate
DOInot available

Abstract

fetched live from OpenAlex

© 2003 Hamel et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL. prostate cancerBRCA1BRCA2founder mutations Background: Relatives of BRCA1 and BRCA2 mutation carriers have long been proposed by epidemiological studies to have an increased risk of developing prostate cancer. In the Ashkenazi Jewish (AJ) population, the existence of 3 frequent founder mutations, 185delAG and 5382insC in BRCA1 and 6174delT in BRCA2 greatly facilitates screening for carriers. Methods: We tested 146 AJ men with confirmed diagnoses of invasive prostate cancer. Thirteen had at least one first degree relative with prostate cancer. The median age at diagnosis of participants was 67.9 years (range 48.6–84.2 years). Subjects were screened for the BRCA1:185delAG, BRCA1:5382insC and BRCA2:6174delT mutations simultaneously using a multiplex sizing assay detecting band shifts in the presence of the variant sequence. Results: Two out of 146 individuals were found to carry the germline BRCA2 mutation 6174delT (1.4%); the previously reported population frequency for this mutation is ~1 % in AJ. We found no

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)0.002
metaresearch head score (Gemma)0.005
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 score0.980
Threshold uncertainty score0.931

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0040.001
Insufficient payload (model declined to judge)0.2780.052

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 head0.072
GPT teacher head0.385
Teacher spread0.312 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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