Bibliographic record
Abstract
There has been no solution to heart disease to date. I obtained discarded veins from bypass (CABG) surgeries and subjected them to phospholipid analysis. We also obtained arterial cells from human umbilical cords and cultured them with a decreasing concentration of either cholesterol or oxidized cholesterol. Patients undergoing CABG surgery and aging swine had significantly higher levels of sphingomyelin in their arterial cells than arterial cells from human umbilical cords. Oxidized low-density lipoprotein (OxLDL) and oxysterols further contribute to atherosclerosis by increasing the synthesis of thromboxane in platelets, a clotting factor. When we incubated arterial cells with cholesterol that had not been oxidized, even at twelve times the concentration of the oxidized cholesterols we used, there was no effect on sphingomyelin content, this shows that cholesterol itself is not the reason for heart disease, and has to be oxidized in order to cause harm. My study indicated that atherosclerosis is due to a diet that contains a high level of oxysterols. Normal levels of oxysterols in the plasma will not increase sphingomyelin levels. Removing oxidized fat from the diet should be considered as a therapeutic measure for atherosclerosis. Ancel Keys, who some consider the father of the cholesterol-heart disease hypothesis said in 1997: "There's no connection whatsoever between the cholesterol in food and cholesterol in the blood."
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.073 | 0.028 |
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".