Numerical simulation of groundwater flow in backfilled open-pits for BDZ deviation performance
Bibliographic record
Abstract
This dataset contains simulated groundwater flow entering multiple backfilled open-pits with mine wastes (flowrate results) and some Python script to visualize the data. The objective was to predict the blast damage zone (BDZ) created by mine excavation on the flowrate through the backfilled wastes. Flowrates were obtained by 3D numerical simulation using PFLOTRAN finite volume code (www.pflotran.org). Conceptual model of the BDZ and equivalent permeability was derived from Rousseau and Pabst (in press) and Mourzencko et al. (2012) (see https://hal.archives-ouvertes.fr/hal-01196684/file/mourzenko2012.pdf). Number of cases simulated: 40500, with 40496 converged numerical simulations. Calculated were performed using the High Performance Computing Ressource of Calcul Quebec (www.calculquebec.ca/) and Compute Canada (www.computecanada.ca/)
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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".