Characterization of Waste Density and Settlement via Micro gravity
Bibliographic record
Abstract
Optimizing the utilization of landfill space and production of biogas, which can be used as an energy source, is dependent on understanding the compaction and stabilization of waste over time. Maximum compaction minimizes the landfill footprint; however, it might not provide the optimal environmental conditions for bacteria development and waste stabilization. This paper reports on a research project which pilots the use of repeated microgravity surveys to map changes in waste density of waste over time in a bioreactor landfill. Over the duration of 3 years, several microgravity surveys will be conducted on a new cell at a bioreactor landfill in Sainte-Sophie, Quebec, Canada, as it is gradually filled with waste up to a height of 25 m. The paper presents a comparison of gravity data acquired in June 2010 (waste height ≈5.5 m) and April 2011 (waste height ≈13 m).
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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 | 0.002 | 0.001 |
| 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".