Oxygen release compound as a chemical treatment for nutrient rich estuary sediments and water
Bibliographic record
Abstract
The objectives of this work were: (i) to evaluate the efficacy of Oxygen Release Compound (ORC), oxygen providing agent that enhance the oxidation of organic matter in fresh water, marine water, and sediment; and (ii) to explore the potential aquatic toxicity that might be generated due to its use. A bench scale laboratory experiments were conducted using five different water sources (2 freshwater, 2 marine water and a deionised water). During the assay, flasks of 1 L capacity were dosed with artificial sediment and ORC and kept at room temperature for 10 days. Temperature, pH, DO, UV254, TOC and Mg were periodically measured. The potential aquatic toxicity that might be generated as a by-product of ORC use was performed. The experimental results reveal that ORC is indeed effective in releasing oxygen over a long period of time and it is also effective for the remediation of natural waters enriched with organic matter. The toxicity test shows that ORC treatment did not create any biological toxicity in freshwater samples (IC50<1 Toxicity Unit-TU). However, marine water samples reveal a high toxicity and had IC50>1 TU. The study proves that ORC was an appropriate technology that can safely be used to treat natural waters enriched with nutrient and natural organic matter.
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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) | 0.001 | 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".