South Bay: implications of the draining of mill pond / review prepared for M. Kalin, Boojum Research Ltd, Toronto
Bibliographic record
Abstract
Mill Pond is located to the east of a topographic divide on the mill site. It receives surface runoff and shallow groundwater discharge. At the northeastern/ eastern part a small dam has been constructed. The surface elevation of the water level in Mill Pond is such, that it is higher than the elevation of the seeps WHS and WHSS. Mill Pond could, therefore, be a source of water contributing to these seeps. Unfortunately, there is neither shallow stratigraphic information nor information with respect to the configuration of the bedrock surface between Mill Pond and the seeps to indicate a potential path for the shallow groundwater. Furthermore, it would be next to impossible to obtain this information, because of the effect of the decommissioning and subsequent landscaping of the mill site. The only way to determine a possible inter-relationship between the seeps and Mill Pond is to drain the pond temporarily and observe the effect of the draining. The experiment was started on June 3, 1998, after a siphon, which drains towards Boomerang Lake, had been installed in the Mill Pond. Daily and on occasion multiple daily measurements were taken of the flow at various locations on the mine site, the water levels in piezometers, shaft, PRC, etc. Furthermore precipitation was recorded, as well as basic chemical parameters were measured and water samples were collected for future analysis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".