Diverse physiological and pharmacological functions of fatty acids
Bibliographic record
Abstract
過去半世紀の食習慣の変化は，健康寿命を延ばす上で十分に寄与したと思われる．しかし，多種の癌の死亡率増加やアレルギー・炎症性疾患の増加，行動パターンの変化なども伴っていた．これらの変化に脂質栄養が深く関わっていると考えられているが，従来の“植物油を善玉とし，動物性脂肪とコレステロールを悪玉とする栄養指導”は，むしろ心疾患を増やし，癌死亡率，総死亡率を上げる危険なものであった．短期間の臨床試験の結果を長期の慢性疾患の予防に直接当てはめてしまったこと，家族性高コレスロール血症のような遺伝的素因を持つ人の多い集団の結果を，一般集団にまでそのまま演繹してしまったこと，疾病と相関の高い因子を危険因子とし，因果関係を考慮することなく，その因子を減らす（低下させる）手段をとってきたことなど，考えるべきことが多い．本総説では，各種脂肪酸が脳機能，メタボリックシンドローム・糖尿病，癌，動脈硬化性疾患，などに及ぼす多様な影響について，基礎・臨床面の最新のデータを紹介しながら，心身の健康増進に寄与しうる脂肪酸のバランスについて解説している．
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".