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Record W2313722541 · doi:10.1097/ruq.0b013e31824bfc06

ACR Appropriateness Criteria® Multiple Gestations

2012· article· en· W2313722541 on OpenAlexaff
Sandra O. DeJesus Allison, Marcia C. Javitt, Phyllis Glanc, Rochelle F. Andreotti, Genevieve L. Bennett, Douglas L. Brown, Theodore J. Dubinsky, Mukesh G. Harisinghani, Robert D. Harris, Donald G. Mitchell, Pari V. Pandharipande, Harpreet K. Pannu, Ann E. Podrasky, Thomas Shipp, Cary L. Siegel, Lynn L. Simpson, Jade J. Wong-You–Cheong, Carolyn M. Zelop

Bibliographic record

VenueUltrasound Quarterly · 2012
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineGestationObstetricsOligohydramniosNonstress testIntrauterine growth restrictionUmbilical cordPregnancyUmbilical arteryGuidelineFetal heart rate

Abstract

fetched live from OpenAlex

Multiple gestations are high-risk compared with singleton pregnancies. Prematurity and intrauterine growth restrictions are the major sources of morbidity and mortality common to all twin gestations. Monochorionic twins are at a higher risk for twin-twin transfusion, fetal growth restriction, congenital anomalies, vasa previa, velamentous insertion of the umbilical cord and fetal death. Therefore, determination of multiple gestation, amnionicity and chorionicity in the first trimester is important. Follow up examinations to evaluate fetal well-being include assessment of fetal growth and amniotic fluid volume, umbilical artery Doppler, nonstress test and biophysical profile. To date, there is a paucity of literature regarding imaging schedules for follow-up. At the very least, antepartum testing in multiple gestations is recommended in all situations in which surveillance would ordinarily be performed in a singleton pregnancy.The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed biennially by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging.

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)0.000
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 score0.336
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.020
GPT teacher head0.289
Teacher spread0.269 · 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

Citations19
Published2012
Admission routes1
Has abstractyes

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