{"id":"W7117579497","doi":"10.1016/j.gsd.2025.101574","title":"Assessing groundwater storage response to snow cover dynamics in large Moroccan river basins over the last decades using remote sensing data","year":2025,"lang":"en","type":"article","venue":"Groundwater for Sustainable Development","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Office Chérifien des Phosphates; Fonds de recherche du Québec; Université Mohammed VI Polytechnique; Québec Ministère du Développement Durable, de l’Environnement et de la Lutte Contre les Changements Climatiques; Centre National pour la Recherche Scientifique et Technique; Fondation OCP; Environmental Systems Research Institute","keywords":"Snowmelt; Groundwater recharge; Groundwater; Hydrology (agriculture); Drainage basin; Snow; Groundwater discharge","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0005318743,0.0002757338,0.0002385856,0.0008932661,0.0003037335,0.0004932967,0.0003328745,0.0003803349,0.0004472555],"category_scores_gemma":[0.0009948992,0.0001230794,0.0003796848,0.0009548505,0.0002228101,0.0004439132,0.0004560637,0.0001606855,0.00009819739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001807955,"about_ca_system_score_gemma":0.0007801192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1534996,"about_ca_topic_score_gemma":0.1971657,"domain_scores_codex":[0.9998429,0.00002721756,0.00001758624,0.00003999502,0.00002273967,0.00004950562],"domain_scores_gemma":[0.9995523,0.00009408047,0.0001432594,0.0000342994,0.0001358249,0.00004022373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001795714,0.00005228622,0.9690673,0.00007539721,0.0002442366,0.0003319637,0.0006466096,0.009182866,0.003848246,0.0002443415,0.0008911222,0.0152361],"study_design_scores_gemma":[0.000005527672,0.00002381476,0.9909438,0.00001356078,0.00005387801,0.0000374322,0.0004291889,0.006791652,0.0005496801,0.00003338092,0.001108635,0.000009451444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998539,0.0001910293,0.00006833382,0.00008712467,0.00000438862,0.00000288956,0.0008577835,0.00000705067,0.0002424914],"genre_scores_gemma":[0.9989506,0.00008195549,0.0001109682,0.00001337023,0.000005656784,0.000004880892,0.0007037307,0.000001666095,0.000127213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1534996,"threshold_uncertainty_score":0.3052123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03065623384814926,"score_gpt":0.2768465043754546,"score_spread":0.2461902705273054,"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."}}