A GIS-based approach for supporting groundwater protection in eskers: Application to sand and gravel extraction activities in Abitibi-Témiscamingue, Quebec, Canada
Bibliographic record
Abstract
Part of Abitibi-Témiscamingue in northwestern Quebec (25,750 km2), within the Quebec/Ontario Clay Belt, Canada. The focus is set on the unconfined granular aquifers found in eskers, the latter containing significant groundwater resources, both in terms of water quality and quantity. Yet, these glaciofluvial deposits also constitute the main source of exploitable sand and gravel and are therefore frequently at the roots of land use conflicts. Methods and indices based on the use of geographic information systems (GIS) were developed in support of land management strategies oriented towards the protection of groundwater resources in eskers of northwestern Quebec. A groundwater resource sensitivity index was defined for each 10 × 10 m parcel of esker on the basis of (1) an evaluation of the aquifer potential based on three geomorphological parameters observable on well-known granular aquifers and (2) estimates of the parameters included in the DRASTIC method. The pressure induced by sand and gravel extraction on the groundwater resources was subsequently evaluated on the basis of (1) the resource sensitivity index, and (2) the spatial density of sand and gravel extraction sites and groundwater wells. These calculations are used to suggest solutions for supporting the sustainable management of sand and gravel extraction activities at the regional scale and for highlighting sectors where field data acquisition is most needed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".