Bibliographic record
Abstract
> Dis-moi ce que tu manges, je te dirai ce que tu es. [Tell me what you eat and I will tell you what you are.] > > Jean Anthelme Brillat-Savarin, 1826 The so-called paleolithic diet has become popular in recent years among some diet enthusiasts. While this diet may soon become one of many passing fads, it is nevertheless true that our human ancestors consumed a diet that was very different from that of today1. The paleolithic diet had about as much cholesterol as is consumed by modern humans, but also contained far more polyunsaturated fat derived from wild game. Our hunter-gatherer ancestors survived by consuming wild game as their primary source of protein. Fat of wild animals contains about 9% eicosapentaenoic acid (EPA) and 5 times more polyunsaturated fat per gram than is found in domesticated livestock2, which contains almost undetectable amounts of omega-3 (also known as n-3) fatty acids (FA). The current FA intake must be properly viewed as a more recent alteration of longstanding dietary patterns to which humans had adapted during tens of thousands of years1,3 (Figure 1). Figure 1. Dietary ingestion of fatty acid species from paleolithic to modern times. From Eaton and Konner, N Engl J Med 1985;312:283–91; and from Simopoulos AP, Boca Raton: CRC Press; 19993; with permission. There are good sources of n-3 FA in certain leafy plants and vegetables as well as flax, canola, soybean, evening primrose, and borage seed oil supplements; walnuts are another good source. These terrestrial n-3 sources contain α-linolenic acid (ALA; 18:3,n-3). The … Address correspondence to Professor J.M. Kremer, The Center for Rheumatology, 1367 Washington Ave., Albany, New York 12206, USA. E-mail: jkremer{at}joint-docs.com
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".