From Problem Statement to Pilot Scale: A Hybrid Passive Treatment System for Landfill Leachate in North Bay, Ontario, Canada
Bibliographic record
Abstract
Passive treatment of landfill leachate is an enticing option for landfill sites since efficient treatment of the leachate generated can continue after the landfill closes and is no longer receiving waste (therefore not generating a profit). Treatment performance in these systems is affected by regional climate and therefore site-specific research needs to be considered for each treatment system design. This three-phase treatability study was designed to determine a pretreatment system that would minimize the size of the subsequent passive treatment system, and to evaluate various passive treatment technologies at both the bench and pilot scales. The results from this treatability study will be used to support the use of passive treatment systems for landfill leachate mitigation in North Bay, as well as serving as a template for other sites in the northern Ontario climate looking to implement passive treatment of landfill leachate.
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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) | 0.002 | 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".