Evaluating odour impacts from a landfilling and composting site: involving citizens in the monitoring
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The City of Montreal operates a large sanitary landfill site within a densely populated urban area. Adjacent to the landfill site is a yard waste composting facility that processes 10,000 metric tons per year using the windrow technique. Over the years, numerous complaints have been received from citizens in the surrounding area regarding odours, particularly during the fall period. Aware of this nuisance, the City of Montreal wanted to identify odour sources, management operations leading to odours, and weather conditions accentuating odours, as well as to quantify actual odour impact. Forty-three (43) citizens living adjacent to this site were recruited and trained to make odour observations during the fall of 2000. This paper presents the methodology used to select and train the citizens chosen to make odour observations, to quantify and to identify odours. It also presents the main results of the study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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