Adsorption of boron from landfill leachate by peat and the effect of environmental factors
Bibliographic record
Abstract
The effect of different environmental factors including drying, shaking, soil-to-solution ratio, competing ions, solution composition, time, pH, and temperature on adsorption of boron from landfill leachate by peat was investigated. The statistical comparison of experimental results showed that shaking of adsorption samples, soil-to-solution ratio, long-term adsorption, and competing ions did not have any significant effect on boron adsorption. However, solution composition, drying of peat prior to adsorption tests, pH, and temperature had a significant effect on the adsorption of boron by peat. Diluting leachate samples with distilled water had a negative effect on the adsorption capacity. Drying peat significantly reduced its boron adsorption capacity. Boron adsorption reached maximum level at a pH range of 9–9.5. Temperature had a negative effect on the adsorption of boron. The results of two-level factorial design experiments showed that pH had the strongest effect on the adsorption of boron by peat. Key words: boron, peat, landfill, leachate, adsorption, pH, temperature, factorial design.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".