A 22-month-old girl with yellow nodules
Bibliographic record
Abstract
A 22-month-old female toddler was referred for yellow skin nodules. These lesions, which emerged gradually over the past 6 months involved the flexor creases but were also present on the ankles, elbows, shoulders and back (Figure 1). Notably, there was no joint involvement or ocular findings. ... The child was born at term in southern India following an uneventful pregnancy and delivery by caesarean section. The child migrated to Canada at 15 months of age, shortly after which her skin lesions first appeared. The child demonstrated normal growth and development, and there were no previous hospitalizations or surgeries. Apart from the noted skin lesions, the physical examination was otherwise unremarkable: a well-nourished appearing girl weighing 10.9 kg (45th percentile) and a height of 81 cm (12th percentile) with pink and well-perfused extremities; no signs of respiratory distress; a chest clear to auscultation; and no hepatosplenomegaly. The general precordial exam was unremarkable, and her blood pressure measured at 103/72 mmHg. The child’s parents hail from a similar region in southern India but are non-consanguineous. Both parents display an elevated total cholesterol and low-density lipoprotein cholesterol (LDL-C) level, and a low–high-density lipoprotein cholesterol (HDL-C) level but are otherwise healthy. Neither parent exhibited ocular nor cutaneous 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".