Properties and nutritional value of wheat bread enriched by hemp products
Bibliographic record
Abstract
Hemp (Cannabis sativa) is annual plant that is native to China and remained as important material for food, industrial and medical purposes. As source of cannabinoids belongs to controversial, but due to its excellent nutritional profile, non-gluten protein, fat and fibre it has potential in bakery products. Addition of 5% - 20% of hemp press cake fine flour and fine wholemeal significantly increased dietary fibre content, but their influence on volume of laboratory baked bread was different. Reflecting actual dosage, both types of hemp press cake flour diminished bun sizes about 6% - 33%; volumes of bread containing hulled wholemeal were comparable to standard (mean 310 mL/100 g vs. 333 ml/100 g, respectively. Only dehulled wholemeal hemp form increased the bread specific volume (6% - 30%), especially as 10% fortification (434 mL/100 g). Six Canadian hemp products were added as 10% and 20% on wheat flour base, comprising fine hemp flour and coarse hemp powder, dehulled whole seeds, hulled hemp seeds with sea salt as well as 50% and 43% hemp protein concentrates (KP1-KP6, respectively). The higher level of KP1, KP2, KP5 and KP6, the lower bread specific volumes were determined (decrease about 9% - 48%). Soft increase in buns size caused by 10% and 20% KP3 (323 and 319 ml/100 g vs. 296 mL/100 g) was insignificant. The effect of KP4 was reversely verifiable, magnifying the parameter about 25% and 17%, respectively. In terms of protein content in bread, a level 11.75% in wheat bread has risen to approx. 14.5% and 18.0% when 10% and 20% of KP3 and KP5, respectively, was included into bread recipe. All six Canadian hemp products increased dietary fibre content in bread, mainly owing to KP4 and both protein concentrates (up to 4 and 3 times, respectively). Incorporation of hemp flour up to the level of 10% positively affected bread sensorial properties.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".