On a Molecular Basis, Investigate Association of Molecular Structure with Bioactive Compounds, Anti-Nutritional Factors and Chemical and Nutrient Profiles of Canola Seeds and Co-Products from Canola Processing: Comparison Crusher Plants within Canada and within China as well as between Canada and China
Bibliographic record
Abstract
The objectives of this study were to: (1) Use molecular spectroscopy as a novel technique to quantify protein molecular structures in relation to its chemical profiles and bioenergy values in oil-seeds and co-products from bio-oil processing. (2) Determine and compare: (a) protein molecular structure using Fourier transform infrared (FT/IR-ATR) molecular spectroscopy technique; (b) bioactive compounds, anti-nutritional factors, and chemical composition; and (c) bioenergy values in oil seeds (canola seeds), co-products (meal or pellets) from bio-oil processing plants in Canada in comparison with China. (3) Determine the relationship between protein molecular structural features and nutrient profiles in oil-seeds and co-products from bio-oil processing. Our results showed the possibility to characterize protein molecular structure using FT/IR molecular spectroscopy. Processing induced changes between oil seeds and co-products were found in the chemical, bioenergy profiles and protein molecular structure. However, no strong correlation was found between the chemical and nutrient profiles of oil seeds (canola seeds) and their protein molecular structure. On the other hand, co-products were strongly correlated with protein molecular structure in the chemical profile and bioenergy values. Generally, comparisons of oil seeds (canola seeds) and co-products (meal or pellets) in Canada, in China, and between Canada and China indicated the presence of variations among different crusher plants and bio-oil processing products.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".