{"id":"W2619527730","doi":"10.5194/hess-22-1543-2018","title":"Quantification of surface water volume changes in the Mackenzie Delta using satellite multi-mission data","year":2018,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"Université de Bordeaux; Ministère de l'Enseignement Supérieur et de la Recherche; Centre National d’Etudes Spatiales; Agence Nationale de la Recherche","keywords":"Delta; River delta; Surface water; Altimeter; Biogeochemical cycle; Water level; Satellite; Environmental science; Arctic; Geology; Satellite imagery; Remote sensing; Hydrology (agriculture); Oceanography; Geography; Cartography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002084044,0.0002518487,0.0001430743,0.001364591,0.0001656961,0.0004291919,0.0001731489,0.0001343803,0.0002254499],"category_scores_gemma":[0.0003268833,0.0001233311,0.0002439154,0.0009321745,0.0001363518,0.0003633193,0.0004071079,0.0001308163,0.00006070875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006535439,"about_ca_system_score_gemma":0.000366704,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0823379,"about_ca_topic_score_gemma":0.1709002,"domain_scores_codex":[0.9999112,0.000007490197,0.000008574746,0.00003173784,0.00002641417,0.00001449416],"domain_scores_gemma":[0.999804,0.00001980556,0.00007364136,0.00002044217,0.00005800388,0.00002415703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000671441,0.00002604782,0.97402,0.00003646077,0.0001044298,0.00008552684,0.0001906382,0.003532627,0.006122108,0.00005291242,0.0002520355,0.01551004],"study_design_scores_gemma":[0.00000158491,0.00001262991,0.9931792,0.000007300597,0.00001473576,0.00002300856,0.0001266464,0.005393496,0.0006930277,0.00001330397,0.0005294682,0.000005580554],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986622,0.00008908752,0.0002459448,0.000008819017,0.000001299316,0.000004281934,0.0006611327,0.00001389441,0.000313305],"genre_scores_gemma":[0.997541,0.00007010769,0.0007977754,0.000004366267,0.000001932646,0.000008321417,0.001400256,0.00000238241,0.0001739201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9176621,"threshold_uncertainty_score":0.1637173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08161515941012923,"score_gpt":0.3074814909036656,"score_spread":0.2258663314935364,"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."}}