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Record W2476997505 · doi:10.12968/bjom.2016.24.8.556

Non-invasive prenatal testing for Down syndrome in general maternity services

2016· article· en· W2476997505 on OpenAlexaff
Victoria Bills, Jenny Ford, Anne M Duffner, Peter Soothill

Bibliographic record

VenueBritish Journal of Midwifery · 2016
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsTrisomyDown syndromeMedicineObstetricsCell-free fetal DNAPrenatal diagnosisPrenatal screeningDna testingFetusAneuploidyPregnancyIntensive care medicinePediatricsBiologyGeneticsPsychiatryChromosome

Abstract

fetched live from OpenAlex

Since its discovery in 1997, the presence of cell-free fetal DNA in the maternal bloodstream has been put to clinical use to detect variety of fetal conditions, in the antenatal period. The use of fetal DNA can offer a highly accurate screen for the presence of Down syndrome (trisomy 21). This has numerous advantages over standard first trimester combined screening for Down syndrome; for example, a reduction in miscarriages due to its non-invasive nature. This article considers a number of issues that need to be resolved before widespread implication of this type of screening into standard NHS practice.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.122
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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