Bibliographic record
Abstract
Metabolic syndrome (MetS) is defined by the presence of abdominal obesity, hypertension, dysglycemia, and dyslipidemia. Many mutations have been discovered that cause rare monogenic components of metabolic syndrome, and association studies have linked common variants with increased risk of MetS and its components. Despite successes in identifying genetic contributors to metabolic syndrome, unexplained heritability exists and copy number variation (CNV) could be responsible for a portion of this variation. As observed with single nucleotide changes, it is likely that both rare and common CNVs will contribute to MetS disease susceptibility. Recent efforts to map CNVs in control populations have given insight into their size, frequency and distribution. However, despite being observed in controls, the reported CNVs could still modulate susceptibility for late-onset complex traitsor produce subtle metabolic phenotypes. Here we examine the overlap between CNVs found in control datasets and genes with functional hypotheses or evidence of previous association to MetS. Secondly, we present the results and methodology of a search for a rare CNV in a high-penetrance Mendelian disorder, namely familial partial lipodystrophy. As methods to identify CNVs increase in precision and accuracy, the prospect of identifying their role in both rare Mendelian and common complex diseases is exciting.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".