{"id":"W3095980029","doi":"10.5194/egusphere-egu2020-12737","title":"Assessing current tank storage state from multi-mission satellite observations to support water management in southern India","year":2020,"lang":"en","type":"article","venue":"","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Current (fluid); Environmental science; Groundwater; Water storage; Irrigation; Water resources; Water supply; Water resource management; Arid; Hydrology (agriculture); Environmental engineering; Engineering; Geology; Oceanography; Ecology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002807862,0.0002832564,0.0001877953,0.001147373,0.0002415744,0.000684563,0.000613869,0.0003046258,0.0003803923],"category_scores_gemma":[0.0007176891,0.0001751691,0.0003239346,0.001904254,0.0002534706,0.0005703005,0.0004539689,0.0002591034,0.0001693365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008200789,"about_ca_system_score_gemma":0.0007857213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1541106,"about_ca_topic_score_gemma":0.2022687,"domain_scores_codex":[0.9998388,0.00002455951,0.00001782941,0.00003696741,0.00003682138,0.00004492538],"domain_scores_gemma":[0.999551,0.0001019627,0.00009798159,0.00004529074,0.0001483398,0.00005539476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003608593,0.0001749402,0.8870166,0.0002756325,0.0002490821,0.0007273309,0.001614884,0.03819556,0.01275112,0.0003689426,0.003324071,0.05494099],"study_design_scores_gemma":[0.00002260229,0.00005998412,0.9324227,0.00004147247,0.0001098213,0.00006635295,0.002489265,0.06088735,0.001956421,0.0001405396,0.001765378,0.00003823327],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958611,0.000116717,0.0006198816,0.0001115526,0.000007415556,0.00001471424,0.001703144,0.0001086496,0.001456863],"genre_scores_gemma":[0.9973019,0.00009355809,0.00106446,0.00001998533,0.000004763953,0.0000121359,0.001302939,0.000008098435,0.0001921158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1541106,"threshold_uncertainty_score":0.3064272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06410736553940743,"score_gpt":0.3035343103177056,"score_spread":0.2394269447782981,"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."}}