Abnormal vertebral segmentation and the notch signaling pathway in man
Bibliographic record
Abstract
Abnormal vertebral segmentation (AVS) in man is a relatively common congenital malformation but cannot be subjected to the scientific analysis that is applied in animal models. Nevertheless, some spectacular advances in the cell biology and molecular genetics of somitogenesis in animal models have proved to be directly relevant to human disease. Some advances in our understanding have come through DNA linkage analysis in families demonstrating a clustering of AVS cases, as well as adopting a candidate gene approach. Only rarely do AVS phenotypes follow clear Mendelian inheritance, but three genes-DLL3, MESP2, and LNFG-have now been identified for spondylocostal dysostosis (SCD). SCD is characterized by extensive hemivertebrae, trunkal shortening, and abnormally aligned ribs with points of fusion. In familial cases clearly following a Mendelian pattern, autosomal recessive inheritance is more common than autosomal dominant and the genes identified are functional within the Notch signaling pathway. Other genes within the pathway cause diverse phenotypes such as Alagille syndrome (AGS) and CADASIL, conditions that may have their origin in defective vasculogenesis. Here, we deal mainly with SCD and AGS, and present a new classification system for AVS phenotypes, for which, hitherto, the terminology has been inconsistent and confusing.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".