{"id":"W1720183865","doi":"10.1016/j.ejrh.2015.05.015","title":"A GIS-based approach for supporting groundwater protection in eskers: Application to sand and gravel extraction activities in Abitibi-Témiscamingue, Quebec, Canada","year":2015,"lang":"en","type":"article","venue":"Journal of Hydrology Regional Studies","topic":"Soil and Land Suitability Analysis","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université du Québec en Abitibi-Témiscamingue","funders":"Ministère de l'Énergie et des Ressources Naturelles","keywords":"Groundwater; Aquifer; Extraction (chemistry); Resource (disambiguation); Geology; Hydrology (agriculture); Water resource management; Environmental science; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003637265,0.000564022,0.0002327137,0.001830891,0.0009236892,0.001560076,0.0007578882,0.0003584884,0.002905374],"category_scores_gemma":[0.00145072,0.0002087551,0.0002913873,0.002943654,0.0003855207,0.0004343799,0.0005669979,0.0002306188,0.0002437796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01151473,"about_ca_system_score_gemma":0.009074758,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9533235,"about_ca_topic_score_gemma":0.977467,"domain_scores_codex":[0.9997945,0.00004978625,0.00001476605,0.00003715007,0.00006648478,0.00003720407],"domain_scores_gemma":[0.9994596,0.0001727708,0.00004124016,0.0000270505,0.0002229061,0.00007643647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003042248,0.0005843943,0.3293906,0.0007699074,0.0002108105,0.001970189,0.004094271,0.3463,0.01247479,0.005675976,0.01300687,0.2852179],"study_design_scores_gemma":[0.00007958398,0.00008469692,0.2206024,0.0001116131,0.00007308618,0.0001571981,0.01059262,0.7514045,0.00267069,0.001033027,0.01310541,0.00008519188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9268878,0.0003941938,0.03362218,0.0009145405,0.00001837063,0.001244541,0.01312235,0.002304839,0.02149122],"genre_scores_gemma":[0.9022548,0.0003985397,0.08897491,0.00005009094,0.000005985175,0.0002524713,0.0040864,0.00005518944,0.003921578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04667652,"threshold_uncertainty_score":0.09390277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0340648851882451,"score_gpt":0.2808213256886669,"score_spread":0.2467564405004218,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}