Practical applications for global positioning system data from solid waste collection vehicles
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
Studies of municipal solid waste collection systems have traditionally relied upon information collected from time and motion studies or truck logs. This type of data collection has been expensive, the volume of data collected has been small, and the reliability of the data has been suspect. A recent project in Hamilton, Ontario, monitored five municipal solid waste collection vehicles using a global positioning system (GPS) as an alternative to traditional data collection methods. The study found that the GPS data are reliable, accurate, and suitable for a range of solid waste planning purposes. Data collection was automatic and relatively inexpensive. Analysis of the data identified significant differences in the performance of the vehicles on different routes. Data collection using GPS is an improvement over traditional data collection methods, but the large volume of data generated will provide challenges for waste managers. Key words: data collection, global positioning system, municipal solid waste, refuse collection, automatic vehicle location.
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 | 0.000 |
| 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 it