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Record W3037990761 · doi:10.2217/pme-2019-0136

Public Interest in Whole Genome Sequencing and Information Needs: An Online Survey Study

2020· article· en· W3037990761 on OpenAlexaffabout
Holly Etchegary, Brenda J. Wilson, Proton Rahman, Charlene Simmonds, Daryl Pullman

Bibliographic record

VenuePersonalized Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWhole genome sequencingPersonal genomicsGenomeData sciencePublic healthDNA sequencingGenomicsComputational biologyWorld Wide WebBiologyComputer scienceMedicineGeneticsGene

Abstract

fetched live from OpenAlex

Aim: To survey the general public about whole genome sequencing interest, including pharmacogenomic testing, and to identify information important for sequencing decisions. Patients & methods: An online survey of 901 members of the general public in an eastern Canadian province. Results: Interest in whole genome sequencing, including pharmacogenomic testing, was high with few differences among demographic variables. Issues identified as very important to sequencing decisions included familial implications of testing, whether treatment was available for conditions tested and knowing who could access genomic information. Most respondents would value support when interpreting sequencing results. Conclusion: Findings reveal the kind of information and support users of sequencing services would value and could inform the implementation of sequencing into care in ways that accord with public preferences and needs.

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)0.004
metaresearch head score (Gemma)0.013
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.682

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.816
GPT teacher head0.543
Teacher spread0.273 · 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

Citations12
Published2020
Admission routes2
Has abstractyes

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