Heavy Metal and Phosphorus Removal from Waters by Optimizing Use of Calcium Hydroxide and Risk Assessment
Why this work is in the frame
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Bibliographic record
Abstract
The optimizing using calcium hydroxide to remove dissolved heavy metal, phosphorus pollutants and algae was investigated. It was found that the concentration of calcium ion was minimal at pH 10.5 when a large amount of generated calcium carbonate increased the particle size of the precipitates and improved sedimentation of sludge and the removal efficiency of heavy metal and phosphorus significantly. Regardless of the initial heavy metals concentrations contained in the wastewater, the final treated concentrations were all extremely low. Risk assessment in alkaline environment of pH 10.5 was tested by fancy carp, daphnia, seed, luminescent bacterium Q67. The results showed that pH 10.5 had a little influence on the four tested organisms. Thus it is suggested that calcium hydroxide at pH 10.5 may be a potential method for treating wastewater and eutrophication water.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it