Characteristics of urban chemical spills in Southern Ontario
Bibliographic record
Abstract
Thousands of chemical spills occur as a result of accidents or natural disasters each year worldwide and have the potential to harm human health and the environment. More than 700 recorded chemical spills involving more than 1,000 types of chemical occur every year in Southern Ontario, resulting in multiple environmental impacts. This paper presents characteristics of urban chemical spills (1988–2007) and an ArcGIS-based spatial distribution in Southern Ontario. Eleven regions involving 77 municipalities had experienced chemical spills during the study period. Industrial plants accounted for the majority of occurred spills. The St Clair River and the Humber River were the two major rivers encompassing higher spill areas owing to the high density of industry surrounding them. Pipe/hose leaks both accounted for the highest proportion of total chemical spills and resulted in a largest portion of chemical spills causing surface water impacts. The analysis results will provide information for a further study to develop a comprehensive urban chemical spill management strategy, which emphasizes spill prevention, control and emergency response. The strategy could also be used to assist both municipalities and industries to minimize the potential spill impacts to the environment and public health and to better protect water resources.
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.
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 | 0.049 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".