Human Health Risk Assessment Approach for Urban Park Development
Bibliographic record
Abstract
A Human Health Risk Assessment (HHRA) was undertaken for a proposed park development "River Landing", to be constructed along the north bank of the South Saskatchewan River in the City of Saskatoon, Saskatchewan, Canada. The purpose of the HHRA was to determine whether chemical constituents identified at the site, including polycyclic aromatic hydrocarbons (PAHs), petroleum hydrocarbons (PHCs), and toxic and heavy metals, would adversely affect the health of construction workers and potential park users. Although more traditional remediation options were considered, the risk assessment approach was chosen since it represented the best available technology. The HHRA was undertaken using protocols and methodologies proposed and readily accepted by the Canadian Council of Ministers of the Environment (CCME), Health Canada, and the United States Environmental Protection Agency (US EPA). Results of the risk assessment revealed that the magnitude and distribution of the chemicals at the site were such that extensive remediation was not required, and that the site could be developed without any significant restrictions on the proposed use. The assessment revealed that potential exposure to soil constituents would not result in adverse health risk to construction workers involved in park development or future park users.
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 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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".