Monitoring of the Ice Cover within the Scope of the Eastmain-1-A/Sarcelle/Rupert Hydro Power Project
Bibliographic record
Abstract
Implementation of a hydroelectric power project is subject to many conditions and commitments related to environmental protection. Within the scope of the Eastmain-1-A/Sarcelle/Rupert project and in collaboration with the local communities, Hydro-Québec has developed an environmental monitoring program including the follow-up of the ice cover over the course of several winters. The ice monitoring program has begun in the winter of 2009-2010 and is still ongoing. It involves monthly surveys from December to April, and covers a broad territory with 650 km of waterways including stretches of rivers (reduced/increased flow), diversion reaches, lakes, reservoirs and the Rupert Bay. During each survey, the entire territory was flown over by helicopter in order to map the ice cover and to survey the ice thickness at seven transects. The results showed that the diversion reaches and the increased-flow river sections freeze later than the other areas. The lacustrine increased-flow sections (i.e. reservoir) behave almost like the lakes in the area, except for the preferential channels and narrows. The reduced-flow river section (Rupert River downstream from the dam) is influenced by a series of structures built to maintain an upstream water level similar to the pre-diversion level, resulting in an intermediate ice regime that falls between the lacustrine and river regimes. Rupert Bay is strongly influenced by oceanographic and weather factors that affect, control and modify the properties of the ice fields. The bay seems to be unaffected by the hydraulic changes in the river after diversion.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".