Variation of composition and functional properties of gum from six Canadian flaxseed (<i>Linum usitatissimum</i> L.) cultivars
Bibliographic record
Abstract
Summary Flaxseed gum (FG) was prepared from six Canadian flaxseed (Linum usitatissimum L.) cultivars. Yield, neutral sugar content, acidic sugar content and protein content varied significantly among cultivar FG extracts. Zeta potential (−16.4 to −27.4 mV) and rheological properties of solution were cultivar dependent. Solutions prepared with CDC Glas FG had the highest viscosity (2.984 Pa•s), while CDC Sorrel produced the lowest (0.048 Pa•s). FG solutions exhibited pseudoplastic shear‐thinning behaviour. Viscosity of FG solution increased with concentration, while viscosity and pseudoplasticity decreased with increased temperature. NaCl addition decreased solution viscosity while adding sucrose increased viscosity. FG solutions prepared from Flanders and CDC Sorrel had the highest and lowest emulsion activity index, respectively, while solutions of CDC Arras and CDC Bethune FG had the lowest and highest emulsion stability, respectively. Findings presented here provide information that could enable greater utilisation in food, cosmetic and pharmaceutical industries as thickeners and/or emulsifiers.
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.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".