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Record W1988368068 · doi:10.1097/ruq.0000000000000044

ACR Appropriateness Criteria® Second and Third Trimester Bleeding

2013· article· en· W1988368068 on OpenAlexaff
Ann E. Podrasky, Marcia C. Javitt, Phyllis Glanc, Theodore J. Dubinsky, Mukesh G. Harisinghani, Robert D. Harris, Nadia J. Khati, Donald G. Mitchell, Pari V. Pandharipande, Harpreet K. Pannu, Thomas Shipp, Cary Siegel, Lynn L. Simpson, Darci J. Wall, Jade J. Wong-You–Cheong, Carolyn M. Zelop

Bibliographic record

VenueUltrasound Quarterly · 2013
Typearticle
Languageen
FieldMedicine
TopicMaternal and fetal healthcare
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicinePlacenta previaPlacenta accretaVaginal bleedingPlacental abruptionExpert opinionObstetricsPregnancyMagnetic resonance imagingRadiologyIntensive care medicinePlacentaGestation

Abstract

fetched live from OpenAlex

Vaginal bleeding occurring in the second or third trimesters of pregnancy can variably affect perinatal outcome, depending on whether it is minor (i.e. a single, mild episode) or major (heavy bleeding or multiple episodes.) Ultrasound is used to evaluate these patients. Sonographic findings may range from marginal subchorionic hematoma to placental abruption. Abnormal placentations such as placenta previa, placenta accreta and vasa previa require accurate diagnosis for clinical management. In cases of placenta accreta, magnetic resonance imaging is useful as an adjunct to ultrasound and is often appropriate for evaluation of the extent of placental invasiveness and potential involvement of adjacent structures. MRI is useful for preplanning for cases of complex delivery, which may necessitate a multi-disciplinary approach for optimal care.The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every two years 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 and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

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)0.006
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.046
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0150.006

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 head0.014
GPT teacher head0.270
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2013
Admission routes1
Has abstractyes

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