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Record W2001786222 · doi:10.1186/1472-6874-7-3

Time to decide about risk-reducing mastectomy: A case series of BRCA1/2 gene mutation carriers

2007· article· en· W2001786222 on OpenAlexafffund
Mary McCullum, Joan L. Bottorff, Mary T. Kelly, Stephanie Kieffer, Lynda G. Balneaves

Bibliographic record

VenueBMC Women s Health · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaBC Cancer Agency
FundersCanadian Institutes of Health Research
KeywordsBreast cancerMedicineMastectomyGynecologyPsychologyCancerInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The purpose of this research was to explore women's decision-making experiences related to the option of risk-reducing mastectomy (RM), using a case series of three women who are carriers of a BRCA1/2 gene mutation. METHODS: Data was collected in a pilot study that assessed the response of women to an information booklet about RM and decision-making support strategies. A detailed analysis of three women's descriptions of their decision-making processes and outcomes was conducted. RESULTS: All three women were carriers of a BRCA1/2 gene mutation and, although undecided, were leaning towards RM when initially assessed. Each woman reported a different RM decision outcome at last follow-up. Case #1 decided not to have RM, stating that RM was "too radical" and early detection methods were an effective strategy for dealing with breast cancer risk. Case #2 remained undecided about RM and, over time, she became less prepared to make a decision because she felt she did not have sufficient information about surgical effects. Case #3 had undergone RM by the time of her second follow-up interview and reported that she felt "a load off (her) mind now". CONCLUSION: RM decision making may shift over time and require decision support over an extended period.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.291
Teacher spread0.280 · 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 teacher head, 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

Citations23
Published2007
Admission routes2
Has abstractyes

Explore more

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