ACR Appropriateness Criteria® Multiple Gestations
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".