Examining the Effects of Covered Landfills on Gas Emissions in Parc Baldwin, Montreal
Bibliographic record
Abstract
Background: Within recent years, parks built on top of former landfills have come under scrutiny for their effectiveness at mitigating the effects of the landfill underneath. The purpose of this study is to identify the biogas emissions of converted landfills nearly a century after landfill closure. Methods: Soil and air emissions for methane and carbon dioxide were collected at 112 sites within the North and South portions of Parc Baldwin in Montreal, Quebec, as well as the presumed boundaries of the former landfill. Results: Overall, it was found that South Baldwin and the immediate area (previously a landfill) had a higher mean average methane concentration, as well as a greater number of sites with methane present than North Baldwin. Particular raised areas in South Baldwin showed anomalously high carbon dioxide concentrations. There was a large degree of heterogeneity between emissions at different sites. Limitations: The Eagle 2 machine is limited to measuring only up to 5,000 ppm or 0.5% volume. Another difficulty with the variation in collection of the data is the differences in collection dates. Conclusions: Ultimately, while South Baldwin did have higher CO2 and methane emissions compared to its counterpart, it is inconclusive whether or not this phenomenon is related to the landfill or other factors. Gas concentrations were significantly below the lower explosive limit in both parks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".