Prospect of Fe non-heme on coffee flour made from solid coffee waste: Mini review
Bibliographic record
Abstract
Abstract Coffee flour (CF) from coffee pulp or husk, solid waste of coffee processing have launched in Canada since 2015. This product is claimed as certified of gluten-free, vegan, kosher, paleo, and non-GMO. Coffe flour is stated to contain three times Fe content than fresh spinach (Spinacia oleracea L.). Several receipts of cookies, donuts, and cakes using CF has been introduced as wheat flour substitution. However, the scientific publication of CF impact for health does not appear until August 2018 yet. A review has been carried out using data on Google with a maximum publication age of 15 yr. This Fe non-heme prospect is allegedly unable to be absorbed optimally by the organism. Coffee pulp and husk contain an inhibitor, such as caffeine, polyphenol, calcium, dietary fiber, manganese, magnesium, and zinc; which detain Fe absorption. On the other hand, the promoter/enhancer of Fe absorption such as vitamin C, vitamin A, and amino acid was decreased in CF processing. Several types of research have to be conducted to tackle this problem in Faculty of Medicine and Faculty of Agriculture and Animal Husbandry University Muhammadyah of Malang, Indonesia.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".