Decontamination of water polluted with oil through the use of tanned solid wastes
Bibliographic record
Abstract
Sorption by natural organic substrates, inorganic materials or synthetic fibers is one of the most popular methods used for the separation of oily wastes from contaminated water. In this work, the ability of chrome shavings (CS) and of buffing dusts of crust leather (BDCL) to remove motor oils and oily wastes from demineralised water and natural seawater has been studied. Tannery solid wastes are formed mainly by proteins and have a highly organized structure in the form of fibers (ΦΦ: 100 nm). These wastes have a high oil sorption capacity. Tanned solid wastes are capable of absorbing many times their weight in oil (6.5–7.6 and 12.8–14.5 g/g dry substrate, respectively, for ground CS and BDCL). The sorption capacity depends strongly of sorbent nature. The removal of oils from the water surface is a quasi-instantaneous process. After use, the saturated waste floats and can be removed in an efficient and easy manner. The results look fairly promising as to possibilities of using tanned wastes to remove oils from industrial effluents and from contaminated coastal areas.
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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) | 0.000 | 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".