Prenatal findings in 11 cases with craniofacial microsomia using the Alberta Congenital Anomalies Surveillance System, 1997–2019
Bibliographic record
Abstract
Craniofacial microsomia (CFM) primarily includes specific head and neck anomalies that co-occur more frequently than expected. The anomalies are usually asymmetric and affect craniofacial features; however, there are frequently additional anomalies of variable severity. Published prenatal findings for CFM are limited. This study contributes 11 cases with CFM and their anomalies identified prenatally. Cases born between January 1, 1997 and December 31, 2019 with CFM were abstracted from the Alberta Congenital Anomalies Surveillance System, which is a population-based program ascertaining congenital anomalies for livebirths, stillbirths, and termination of pregnancies for fetal anomalies. There were 11 cases ascertained with prenatal findings including facial anomalies: one each with left cleft lip, right microtia, and bilateral microphthalmia. Two cases had vertebral anomalies. In addition, anomalies of the kidneys, brain, heart, and radial ray were identified. Six (55%) had a single umbilical artery, five (45%) were small for gestational age, and three (27%) were from a twin pregnancy that were discordant for anomalies. Four (36%) overlapped another proposed recurrent constellations of embryonic malformation condition. This study describes prenatal findings for 11 cases with CFM. Comparable to prior published cases, there were recurring anomalies on prenatal imaging, including anomalies of the brain, eye, heart, kidneys, and radial ray, which may aid in the prenatal diagnosis of CFM.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".