Pretreatment of poultry manure anaerobic-digested effluents by electrolysis, centrifugation and autoclaving process for<i>Chlorella vulgaris</i>growth and pollutants removal
Bibliographic record
Abstract
Different pretreatments (electrolysis, centrifugation and autoclaving) coupled with Chlorella vulgaris biological system was used for the treatment of poultry manure anaerobic-digested effluents. The pretreated effluents were used as the growth medium for algal cultivation. The pollutant removal efficiencies of the combined treatments were determined. Electrochemical pretreatment can efficiently remove the ammonia (NH4+), total phosphorus (TP), total organic carbon (TOC), total carbon (TC), turbidity and bacteria in the digested effluents. About 100.0% NH4+, turbidity and bacteria, 97.6% TP, 81.5% TOC and 96.6% inorganic carbon were removed by 5-h electrochemical treatment. The maximal algal biomass accumulation (0.53 g L(-1)) was obtained from culture in the effluents pretreated with 2-h electrolysis. The pollutants removal amounts by the combination of electrolysis and biological treatment were much higher than the other combinations.
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) | 0.000 | 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 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".