The 22q11.2 deletion syndrome as a model for idiopathic scoliosis – A hypothesis
Bibliographic record
Abstract
Adolescent idiopathic scoliosis (AIS), defined as a lateral deviation of the spine of at least ten degrees, is a classic enigma in orthopaedics and affects 1-4% of the general population. Despite (over) a century of intensive research, the etiology is still largely unknown. One of the major problems in all existing AIS research is the fact that most patients come to medical attention after onset of the curve. Therefore, it is impossible to know whether current investigated parameters are causative, or an effect of the scoliosis. Moreover, up until now there is no known animal model that captures the core features of AIS. In order to identify causal pathways leading to AIS we propose another approach, which has been of great value in other medical disciplines: To use a subset of the population, with a higher risk for a certain disease as a "model" for the general population. Such a "model" may allow the identification of causative mechanisms that might be applicable to the general population. The 22q11.2 deletion syndrome (22q11.2DS) is the most common microdeletion syndrome and occurs in ∼1:3000-6000 children and 1:1000 pregnancies. Nearly half of the population of patients with 22q11.2DS develop a scoliosis that in most cases resembles AIS as far as age at onset and curve pattern. We postulate that within 22q11.2DS certain causal pathways leading to scoliosis can be identified and that these are applicable to the general population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".