Noonan Syndrome: Clinical Features, Diagnosis, and Management Guidelines
Bibliographic record
Abstract
Noonan syndrome (NS) is a common, clinically and genetically heterogeneous condition characterized by distinctive facial features, short stature, chest deformity, congenital heart disease, and other comorbidities. Gene mutations identified in individuals with the NS phenotype are involved in the Ras/MAPK (mitogen-activated protein kinase) signal transduction pathway and currently explain ∼61% of NS cases. Thus, NS frequently remains a clinical diagnosis. Because of the variability in presentation and the need for multidisciplinary care, it is essential that the condition be identified and managed comprehensively. The Noonan Syndrome Support Group (NSSG) is a nonprofit organization committed to providing support, current information, and understanding to those affected by NS. The NSSG convened a conference of health care providers, all involved in various aspects of NS, to develop these guidelines for use by pediatricians in the diagnosis and management of individuals with NS and to provide updated genetic findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".