Bibliographic record
Abstract
カナダ保健省は健康な成人におけるカフェインの1 日あたりの悪影響のない最大摂取量を400mgとしている。近年，清涼飲料水にはカフェインを多く含むものもあり，わが国でも過剰摂取に関する注意喚起がされている。清涼飲料水中のカフェイン含有量を調べたところ，エナジードリンク（5製品）が0.14～0.37mg/mL，緑茶（一般飲料3製品，機能性表示食品4製品，特定保健用食品4製品）が0.05～0.21mg/mL，コーヒー（一般飲料3製品，特定保健用食品2製品）が0.22～0.47mg/mL，コーラ（一般飲料4製品，特定保健用食品3製品）が0.04～0.13mg/mLであった。エナジードリンクと一般飲料の1製品（1本）あたりのカフェイン量は，エナジードリンク（容量：250 ～500mL）が65～131mg，緑茶（525～600mL）が58～72mg，コーヒー（275～600mL）が112～204mg，コーラ（350～1500mL）が21～78mgであった。機能性表示食品と特定保健用食品の一日摂取目安量あたりのカフェイン量は，緑茶（350～1200mL）が39～216mg，コーヒー（185～280mL）が57～62mg，コーラ（470～490mL）が20～53mgであった。エナジードリンクや一般飲料のコーヒーは，2，3 本飲むことで400mg 前後のカフェイン摂取量になる製品があり，過剰摂取には注意が必要と考えられる。We investigated by HPLC the caffeine content of beverages. The contents of caffeine in energy drinks (5 products), green teas (green tea: 3 products, food with functional health claims: 4 products, foods for specified health use: 4 products), coffees (coffee: 3 products, foods for specified health use: 2 products) and cola drinks (cola: 4 products, foods for specified health use: 3 products) were 0.14～0.37, 0.05～0.21, 0.22～0.47 and 0.04～0.13 mg/ mL, respectively. The intakes of caffeine from energy drinks (250～500 mL/bottle), green teas (525～600 mL/ bottle), coffees (275～600 mL/bottle) and colas (350～1500 mL/bottle) are estimated to be 65～131, 58～72 , 112～204 and 21～78 mg, respectively. When the food with functional health claims and foods for specified health use were consumed as indicated on the label, the daily intakes of caffeine from green tea (350～1200 mL), coffee (185～280 mL) and cola drink (470～490 mL) were 39～216, 57～62 and 20～53 mg, respectively. In Canada, the recommended maximum caffeine intake for healthy adults is 400 mg/day. Therefore, the possibility of excessive intake of caffeine from energy drinks and coffees should be considered.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.011 |
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".