Pediatric decision limits for lipid parameters in the Brazilian population
Bibliographic record
Abstract
Disorders of lipid and lipoprotein metabolism are commonly observed in obese and insulin resistant states, and are often referred to as diabetic dyslipidemia.Diabetic dyslipidemia is characterized by high plasma triglycerides, reduced highdensity lipoprotein cholesterol (HDL-C), and increased levels of small dense low-density lipoprotein (LDL) particles, which collectively increase the risk of premature atherosclerosis and cardiovascular disease.These lipid abnormalities result from overproduction of triglyceride-rich hepatic and intestinal lipoproteins, which are rapidly metabolized to generate highly atherogenic remnant lipoprotein particles.While cardiovascular complications are often only observed later in adulthood, the genesis of atherosclerosis begins in childhood and cardiovascular risk factors early in life are associated with increased carotid intima-media thickness (CIMT), a non-invasive measure of subclinical atherosclerosis, 1 as well as increased severity of atherosclerosis measured at
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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".