A patient’s informative mistake: niacin is very effective in correcting dyslipidaemia: Table 1
Bibliographic record
Abstract
A 72-year-old man at high risk for cardiovascular disease, with a history of peripheral vascular disease and type 2 diabetes, presented with lipids above targets despite maximum daily treatment with atorvastatin 80 mg, fenofibrate supra 160 mg daily, and ezetimibe 10 mg. His low density lipoprotein cholesterol (LDL-C) was 2.6 mmol/l, total cholesterol: HDL ratio 5.6, and high density lipoprotein cholesterol (HDL-C) 0.9 mmol/l. Because his lipids were not within target, he was advised to start 2250 mg of niacin in three divided doses daily. For 5 months, he mistakenly took 2250 mg of niacin three times daily, a consumption of 6750 mg/day! The effects on his lipids were: HDL-C increased nearly 100% to 1.7 mmol/l, LDL-C decreased by 50% to 1.3 mmol/l, and cholesterol: HDL ratio decreased by over 50% to 2.1. His excessive intake dramatically demonstrates the positive effect of niacin on lipids. Fortunately he did not suffer adverse effects from taking more than the recommended limit of 3000 mg/day.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".