Cellulases: From Bioactivity to a Variety of Industrial Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Utilization of microbial enzymes has been widely reported for centuries, but the commercial use of enzymes has been recently adopted. Particularly, cellulases have been utilized in various commercial sectors including agriculture, brewing, laundry, pulp and paper and textile industry. Cellulases of microbial origin have shown their potential application in various commercial sectors including textile, pulp and paper, laundry, brewing, agriculture and biofuel. Cellulases have diversified applications in the food industry, food service, food supply and its preservation. Indeed, cellulases can tenderize fruits, clarify the fruit juices, reduce roughage in dough, hydrolyze the roasted coffee, extract tea polyphenols and essential oils from olives and can increase aroma and taste in food items. However, their role in food industries has by and large remained neglected. The use of immobilized cellulases has further expanded their application in fruit and vegetable processing as it potentiates the catalytic power and reduces the cost of process. Technological and scientific developments will further expand their potential usage in the food industry.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it