Petroleum Refinery Secondary Effluent Polishing Using Freezing Processes—Toxicity and Organic Contaminant Removal
Bibliographic record
Abstract
A petroleum refinery secondary effluent was treated using two freezing techniques--spray freezing and unidirectional downward freezing (UDF). The freezing processes were effective to remove toxicity and total organic carbon (TOC)- and chemical oxygen demand (COD)-causing materials in the effluent. Agitation of the liquid during UDF significantly improved the impurity separation efficiency; 85 to 96% removal of TOC and COD was achieved without any pretreatment and freezing only 70% of the feed water. The treatment efficiency of the spray freezing was at the same level as that of UDF without mixing. The spray ice with longer storage time released more contaminants with early meltwater. The initial contaminant concentration of the feed water and the freezing temperatures (-10 degrees C and -25 degrees C) had no significant influence on the treatment efficiency. A small fluctuation in effluent TOC concentration caused a dramatic change in effluent toxicity (Microtox). The effective concentration (EC20) (Microtox) was effective in detecting effluent toxicity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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".