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Record W4414688284 · doi:10.3138/cjms-2025-0001

Understanding obstetrical soft markers: Significance and implications in 2025

2025· article· en· W4414688284 on OpenAlex
Susan Burnett-Roy

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venue˜The œCanadian journal of medical sonography. · 2025
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsAneuploidyMedical screeningGenetic testingRelevance (law)Prenatal screeningPregnancyRisk assessmentMEDLINE

Abstract

fetched live from OpenAlex

Over the past two decades, prenatal screening options have advanced considerably. Ultrasound soft markers and serum screening have long served as the foundation for non-invasive aneuploidy risk assessment. The advent of cell-free DNA (cfDNA) testing has further enhanced the ability to screen for common aneuploidies, offering the most accurate single screening method for trisomies 21, 18, and 13. The Society of Obstetricians and Gynaecologists of Canada (SOGC) first published guidelines on soft markers in 2005, with subsequent updates in 2017 and 2024, reflecting ongoing changes in screening recommendations. Consequently, the role of ultrasound soft markers has shifted. Many isolated soft markers are no longer considered statistically significant. This article will review recent developments and their relevance to current sonographic practice, emphasizing the continued importance of soft markers in identifying chromosomal abnormalities.

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.

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)0.001
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: none
Teacher disagreement score0.761
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.299
Teacher spread0.243 · 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