Genetic Overview of Syndactyly and Polydactyly
Bibliographic record
Abstract
Syndactyly and polydactyly-respectively characterized by fused and supernumerary digits-are among the most common congenital limb malformations, with syndactyly presenting at an estimated incidence of 1 in 2,000-3,000 live births and polydactyly at a frequency of 1 in approximately 700-1,000 live births. Despite their relatively regular manifestation in the clinic, the etiologies of syndactyly and polydactyly remain poorly understood because of their phenotypic and genetic diversity. Further, even though concrete knowledge of genotypic links has been established for some variants of syndactyly and polydactyly, there appears to be no single comprehensive published summary of all syndromic and nonsyndromic syndactyly and polydactyly presentations, and there is decidedly no resource that maps all syndromic and nonsyndromic syndactylies and polydactylies to their genetic bases. This gap in the literature problematizes comprehensive carrier screening and prenatal diagnosis and complicates novel diagnostic attempts. This review thus attempts to collect all that is known about the genetic bases of syndromic and nonsyndromic syndactylies and polydactylies, as well as to highlight the dactyly manifestations for which no genetic bases are as yet known. Then, having established a summation of existing and missing knowledge, this work briefly outlines the diagnostic techniques that a genetics-reinforced understanding of syndactyly and polydactyly could inform.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.003 | 0.001 |
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".