TREATMENT OF LOG YARD RUNOFF USING A RECIRCULATING SAND FILTRATION PROCESS
Bibliographic record
Abstract
A re-circulating filtration process using oxide-coated sand successfully removed COD and turbidity from log yard runoff. After passing only one pore volume of the runoff through the sand column, 72% COD was removed. The 2.4% Fe and Al oxide coating on the sand contributed to better COD removal than was obtained when the sand was stripped of oxide coating (86% versus 52%, respectively), at least initially before saturation of adsorption sites on the oxide coating occurred. The best COD removal performance came from conditioned sand. This sand, from the same original source and identical to the oxide-coated sand used in all experiments, came from an existing experimental sand column that had been treating log yard runoff for 1 year. The "conditioning" resulted in the sand having a higher TOC content (0.26% wt) and smaller particle sizes. This sand was able to consistently remove 80% COD from repeated batches of log yard runoff with strengths up to 3690 mg l(-1).
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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) | 0.001 | 0.000 |
| 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) | 0.001 | 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".