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Record W3082938210 · doi:10.2217/pme-2020-0026

Universal Tumor Screening for Lynch Syndrome: Perspectives of Patients Regarding Willingness and Informed Consent

2020· article· en· W3082938210 on OpenAlexaffabout
Anusree Subramonian, Doug Smith, Elizabeth Dicks, Lesa Dawson, Mark Borgaonkar, Holly Etchegary

Bibliographic record

VenuePersonalized Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsSt. John’s Health Sciences CentreMemorial University of Newfoundland
Fundersnot available
KeywordsLynch syndromeInformed consentMedicineFamily medicineColorectal cancer screeningColorectal cancerHealth careGenetic testingOncologyInternal medicineAlternative medicineCancerColonoscopyPathologyDNA mismatch repair

Abstract

fetched live from OpenAlex

Aim: Lynch Syndrome is associated with a significant risk of colorectal carcinoma (CRC) and other cancers. Universal tumor screening is a strategy to identify high-risk individuals by testing all CRC tumors for molecular features suggestive of Lynch Syndrome. Patient interest in screening and preferences for consent have been underexplored. Methods: A postal survey was administered to CRC patients in a Canadian province. Results: Most patients (81.4%) were willing to have tumors tested if universal tumor screening were available and were willing to discuss test results with family members and healthcare professionals. The majority (62.6%) preferred informed consent be obtained prior to screening. Conclusion: Patients were supportive of universal screening. They expected consent to be obtained, contrary to current practice across Canada and elsewhere.

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)0.017
metaresearch head score (Gemma)0.049
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: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.049
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.050
GPT teacher head0.310
Teacher spread0.259 · 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

Citations11
Published2020
Admission routes2
Has abstractyes

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