Enzimatic hydrolysis of the raw muscle of nurse shark, Gynglimostoma cirratum
Bibliographic record
Abstract
This paper reports studies on the hydrolysis of the raw muscle of nurse shark, Gynglimostoma cirratum. The material was washed three times with distilled water and diluted in water in a 1:2 muscle/water ratio. The pH was maintaned at 7.,5 and pancreatin, papain or protease were added in the proportions of 0.1%, 0,2%, 0,3%, 0,4% and 0,5% of the total weight of shark muscle. The hydrolysis took place in na agitated aqueous medium at 40°C. The environmental pH was measured at 5, 10, 15, 30, 60, 90 and 120 min. If required, 0,1% NaOH was added to keep the pH at 8.5. The enzymatic reaction rate was determined by the degree of hydrolysis. The statistical analysis showed there to be significant diferences in the results as a function of the enzymes, times and enzymatic concentrations used. The best results were produced with the enzyme pancreatin; otimal reaction times were found at 90 min. and 120 min., and optimal enzymatic concentrations were found at 0,4 and 0,5%. Cost factors suggest the use of pancreatin at 0.4%. By choosing a reaction time of 90 min. there will be less risks of bacterial contamination.
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 | 0.000 | 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".