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Mutation carriers’ perspectives on Lynch syndrome

2013· article· en· W2765123542 on OpenAlexaboutno aff
Helle Vendel Petersen

Bibliographic record

VenueKlinisk Sygepleje · 2013
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
Fundersnot available
KeywordsLynch syndromeMutationGeneticsMedicineBiologyCancerDNA mismatch repairColorectal cancerGene

Abstract

fetched live from OpenAlex

Learning about hereditary cancer may influence an individual’s self-concept, which otherwise represents a complex but stable cognitive structure. Recently, a 20- statement self-concept scale, with subscales related to stigma-vulnerability and bowel symptom-related anxiety, was developed for Lynch syndrome. We compared the performance of this scale in 591 mutation carriers from Denmark, Sweden and Canada. Principal component analysis identified two sets of linked statements—the first related to feeling different, isolated and labeled, and the second to concern and worry about bowel changes. The scale performed consistently in the three countries. Minor differences were identified, with guilt about passing on a defective gene and feelings of losing one’s privacy being more pronounced among Canadians, whereas Danes more often expressed worries about cancer. Validation of the Lynch syndrome self-concept scale supports its basic structure, identifies dependence between the statements in the subscales and demonstrates its applicability in different Western populations.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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 designQualitative
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
Published2013
Admission routes1
Has abstractyes

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