Ontario Ministry of Northern Development and Mines, Sudbury, ON.
Bibliographic record
Abstract
From 1909 to 1968, the Hollinger Mine produced over 53 millions tons of gold tailings stored in a structure referred to as the Hollinger Tailings Stack. Covering some 190 hectares, up to 25 metres deep, with over 600,000 cubic metres of ponded waters and no spillway, the stack placed at risk some 150 mobile homes located at the toe of the structure. Preliminary assessments of the structure’s stability rated the site to be a high hazard. In 1992, the Ontario Ministry of Northern Development and Mines (MNDM) declared the tailings site to be abandoned and requested that the City of Timmins declare the site to be an emergency. These declarations permitted the Crown to enter the property and carry out much needed remediation work over a period of two years. This paper will present in detail the approach used by the MNDM to solve both the legal and technical problems associated with the remediation of the site. Geotechnical analyses and hydrologic modeling results are discussed as well as construction and revegetation techniques used by the contractors. In 1996 and 2000, policy and regulations were amended to enable the Crown to be better equipped to deal with such emergencies and to prevent similar problems from re-occurring in the future.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.145 | 0.021 |
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".