Bibliographic record
Abstract
Sutfactants may be used in remediation of subsoil and aquifer contaminated with hydrophobic compounds. The objectives of this study were to select potentially suitable sUlfactants that solubilize toluene present as a contaminant and to determine the effectiveness of toluene removal from Ottawa sand by the selected surfactants. Material used as the model soil was Ottawa sand and the organic used as model contaminant was toluene. Used experimental methods were separatory funnel experiment and shaker table agitation/centrifugation experiments. Based on the experimental results, the following conclusions were drawn; t) In the surfactant selection, six different surfactants were chosen based on surfactant types, toxicity, and water solubility. These six were focused into two on the basis of HLB and surface tension study, separatory funnel experiment, shaker table and centrifugation experiments. The two most suitable surfactants were Sandopan JA36 (an anionic surfactant), and Pluronic L44 (a non-ionic surfactant). 2) In the shaker table agitation and centrifugation experiments, the highest recovery of the toluene was 96% which was obtained with one surfactant wash plus two water rinses using an anionic surfactant (Sandopan JA36).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".