Evaluation of cattle skin collagen for producing co-extrusion sausage casing
Bibliographic record
Abstract
Co-extrusion is a fully automated sausage production process that employs a continuous stream of collagen dispersion to encase the extruded meat mass to form an endless sausage rope, that is later crimped into links of selected sizes. Fibrous and soluble type I collagen dispersions obtained from bovine skins of animals aged 18–36 months is used as the raw material for these dispersions. In this study, the chemical and physical properties of cattle skin collagen preparations from four sources [American Calf (AC), Dutch Heavy Veal (DHV), Danish Ox and/or Heifer (DOH), and Heavy German Cow (HGC)] were investigated for their potential application as collagen source for co-extrusion. All dispersions exhibited shear-thinning behavior, following a power-law model with k* values for HGC, DHV, AC, and DOH dispersions of 59, 68, 95 and 114 Pa sn*, respectively. Rheological measurements showed for all dispersions a decrease in elasticity and loss modulus at 35–40 °C. SDS-PAGE indicated the presence of α1(I)- and α2(I)-chains of type I collagen for all dispersions. The mechanical strength of the films was 1.6, 1.6, 1.3 and 1.2 MPa for films prepared from AC, DOH, DHV and HGC dispersions, respectively. After crosslinking a 27% reduction of free amine groups was found for HGC and DOH, followed by 26 and 19% for AC and DHV, respectively. Based on the properties of the dispersions and the films in relation to the co-extrusion process AC, DHV and DOH are potentially suitable as an alternative collagen source.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".