Impact of household food processing strategies on antinutrient (phytate, tannin and polyphenol) contents of chickpeas (<i><scp>C</scp>icer arietinum </i><scp>L</scp>.) and beans (<i><scp>P</scp>haseolus vulgaris </i><scp>L</scp>.): a review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Pulses, which include beans and chickpeas, are major constituents of the human diet. They are important sources of energy and nutrients, particularly protein, folate and minerals. However, they also contain antinutrients which bind minerals, mainly iron and zinc, rendering them less bioavailable or unavailable for absorption. The levels of these antinutrients may be reduced by food processing techniques such as soaking and germination. Researchers have used these techniques in a number of studies; however, there is no consensus regarding the optimum processing conditions for reduction in the levels of these antinutrients. Thus, this review was conducted to describe the results of studies on soaking and germination of chickpeas and beans. A systematic search was carried out utilising Food Science and Technology Abstracts ( FSTA ) (1969 to present), Web of Science (1899 to present) and Scopus (1823 to present). A total of thirty‐three articles were reviewed. Both soaking and germination resulted in significant but variable degrees of reduction in levels of antinutrients in most studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it