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Record W1992774732 · doi:10.1136/ebn.5.3.89

Review: breast cancer is associated with a family history of the disease in first degree relatives

2002· letter· en· W1992774732 on OpenAlexaff
Andrea Eisen, Ellen Irwin

Bibliographic record

VenueEvidence-Based Nursing · 2002
Typeletter
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsHamilton Regional Laboratory Medicine ProgramJuravinski Cancer CentreMcMaster University
Fundersnot available
KeywordsBreast cancerFamily historyMedicineGynecologyEpidemiologyCancerDiseaseFirst-degree relativesInternal medicineObstetricsOncology

Abstract

fetched live from OpenAlex

Collaborative Group on Hormonal Factors in Breast Cancer. Familial breast cancer: collaborative reanalysis of individual data from 52 epidemiological studies including 58 209 women with breast cancer and 101 986 women without the disease. Lancet2001 Oct 27; 358 : 1389 –99 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: In women with a family history of breast cancer, how does the pattern of breast cancer in first degree relatives affect the risk of developing the disease? Studies were identified by searching computerised literature databases, reviewing bibliographies of review articles, and contacting experts in the field. Studies were selected if they were cohort or nested case control studies, included ≥100 women with incident invasive breast cancer, and information about reproductive or hormonal factors was sought on each woman. Principal investigators of the included studies were contacted for data on each woman regarding whether any of her first degree female relatives (mother, sisters, or daughters) had been diagnosed with breast cancer and, if so, their age when the diagnosis was made. Data were also collected on the numbers of … [1]: {openurl}?query=rft.jtitle%253DLancet%26rft.stitle%253DLancet%26rft.volume%253D358%26rft.issue%253D9291%26rft.spage%253D1389%26rft.epage%253D1399%26rft.atitle%253DFamilial%2Bbreast%2Bcancer%253A%2Bcollaborative%2Breanalysis%2Bof%2Bindividual%2Bdata%2Bfrom%2B52%2Bepidemiological%2Bstudies%2Bincluding%2B58%252C209%2Bwomen%2Bwith%2Bbreast%2Bcancer%2Band%2B101%252C986%2Bwomen%2Bwithout%2Bthe%2Bdisease.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0140-6736%252801%252906524-2%26rft_id%253Dinfo%253Apmid%252F11705483%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1016/S0140-6736(01)06524-2&link_type=DOI [3]: /lookup/external-ref?access_num=11705483&link_type=MED&atom=%2Febnurs%2F5%2F3%2F89.atom [4]: /lookup/external-ref?access_num=000171940100008&link_type=ISI

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)0.012
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: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0090.015
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.080
GPT teacher head0.299
Teacher spread0.219 · 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
GenreCommentary

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
Published2002
Admission routes1
Has abstractyes

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