Extraction and characterization of collagen with or without telopeptides from chicken skin
Bibliographic record
Abstract
Poultry by-products are not often processed into high-value products. Rather than being transformed into meal for animal feed, a large quantity of chicken skin could be used to produce collagen, which is valued for its unique functional properties. The purpose of this research project was to extract and characterize collagen from chicken skin. Skins were first ground and then were heated to 40 or 60 degrees C to extract the fat. After mechanical separation, the collagen contained in the resulting solid phase was extracted with pepsin or ethylene diamine. Types I and III collagen were then isolated and characterized by SDS PAGE, antigen labeling, determination of tyrosine residues, and transmission electron microscopy. The total collagen content of the skin was recovered from the solid phase following heat treatment at 40 degrees C. Extraction yields varied with the solubilization process: 38.9% of the collagen content in the solid phase was extracted with pepsin and 25.1% with ethylene diamine. Ratios of type I to type III collagen fractionated using NaCl were 74.4:19.8% with pepsin and 62.4:31.7% with ethylene diamine. Characterization tests further revealed the presence of telopeptides solely on ethylene diamine-solubilized collagen. Chicken skin thus appears to be a good alternative source of high-quality collagen.
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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 | 0.000 | 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".