Hydrolysis of oils in the Wadi Hanifah River in Saudi Arabia by free and immobilized <i>Staphylococcus aureus</i> ALA1 lipase
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
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
This study describes the biochemical properties of Staphylococcus aureus lipase immobilized by physical adsorption to assess its role in the biodegradation of oils in the Wadi Hanifah River. After optimization of the immobilization conditions, the recovered enzyme activity was 95% with appreciable increase in stability. The immobilized and free lipase retained 70% and only 10% of the initial activity after a 60‐min incubation at 80 °C, respectively. More than ~40% residual activity remained after 48 h of incubation at pH5 to 11. The immobilized enzyme retained 100% of the initial activity when used for four cycles and 42% of initial activity when stored at 25 °C for 120 days. Enzyme stability was enhanced in the presence of inactivating agents including β‐mercaptoethanol, SDS, EDTA, and Co 2+ . The bioremediation potential of lipid‐rich wastewater by the immobilized and free lipases was explored by analyses of chemical oxygen demand and lipid content. Both free and immobilized lipases efficiently hydrolyzed all oils tested and organic matter present in the wastewater. Overall, the results indicate the potential of immobilized S. aureus lipase in biological wastewater treatment and offer new options for several industrial applications. © 2018 American Institute of Chemical Engineers Environ Prog, 38:e13000, 2019
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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