Multivariate optimization and kinetics for treatment of fracturing flowback fluids with Chlorella vulgaris
Bibliographic record
Abstract
Fracturing flowback fluids were biologically treated with Chlorella vulgaris. Individual and interactive effects of three variables -the dilution ratio of fracturing flowback fluids, the -mannanase dose, and the powder activated carbon (PAC) dose -on chemical oxygen demand (COD) removal efficiency and algal density were optimized by response surface methodology combined with a Box-Behnken design. Treatment efficiency and algal density were affected most by the dilution ratio. Optimal conditions for algal growth and proliferation comprised a dilution ratio of 1:3, no -mannanase, a PAC dose of 50 mg/L, and a maximum algal density was 2.51 g/L. The experimental data agreed well with the model-predicted COD removal efficiency (42.61% vs. 45.27%) under the optimum conditions of a dilution ratio of 1:5, a -mannanase dose of 135.28 mg/L, and a PAC dose of 50 mg/L. A kinetic equation representing organic compound biodegradation by C. vulgaris was established, and the degradation half-life of COD was 132.63 h.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".