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Record W2006982953 · doi:10.1002/ajmg.a.35238

Prenatal testing for Down syndrome: The perspectives of parents of individuals with Down syndrome

2012· article· en· W2006982953 on OpenAlexafffundabout
Angela Inglis, Catriona Hippman, Jehannine Austin

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2012
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchAGE-WELLNational Down Syndrome Society
KeywordsDown syndromeMedicinePrenatal screeningTest (biology)Family medicinePrenatal diagnosisPediatricsClinical psychologyPregnancyPsychiatry

Abstract

fetched live from OpenAlex

This exploratory, descriptive study examined the views and opinions of parents of individuals with Down syndrome (DS) related to prenatal testing for DS and the use of age-based criteria to determine eligibility for this testing. This survey-based study was designed in collaboration with parents of individuals with DS and the British Columbia-based Lower Mainland Down Syndrome Society (LMDSS). The survey was a 26-item, self-report questionnaire, which was distributed by the LMDSS. Out of the 246 potentially eligible individuals that were mailed surveys, 101 participants returned their completed surveys. The availability of prenatal screening and diagnostic testing for DS was perceived positively by 55.1% and 64.7% of parents, respectively. More than half (60.2%) of participants felt that prenatal diagnostic testing for DS should be available to all pregnant women, regardless of age. In this study, views of Canadian parents of individuals with DS aligned with the prenatal testing policy recently adopted in the USA (whereby any woman, regardless of age or risk factors, can opt for prenatal diagnostic testing) rather than with new Canadian policy (whereby eligibility for diagnostic testing is no longer offered on the basis of age, but on the basis of other risk factors).

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)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.046
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.022
GPT teacher head0.298
Teacher spread0.276 · 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 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

Citations31
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueAmerican Journal of Medical Genetics Part ASame topicPrenatal Screening and DiagnosticsFrench-language works237,207