{"id":"W4323320714","doi":"10.1080/07038992.2023.2178834","title":"Sensitivity Analysis of Parameters of U-Net Model for Semantic Segmentation of Silt Storage Dams from Remote Sensing Images","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Silt; Environmental science; Remote sensing; Sensitivity (control systems); Siltation; Hydrology (agriculture); Geography; Engineering; Geology; Sediment; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009619177,0.0001594067,0.0005634436,0.0006283245,0.00008933974,0.00002353313,0.0001033814,0.00006308837,0.00001058856],"category_scores_gemma":[0.0001267119,0.0001617773,0.0002973941,0.000898,0.0001804022,0.0001902282,0.0000407529,0.0001144181,0.000001386086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002402053,"about_ca_system_score_gemma":0.0001143141,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08592895,"about_ca_topic_score_gemma":0.08586378,"domain_scores_codex":[0.9983206,0.0001303043,0.0006499041,0.0002154688,0.0003798633,0.0003038954],"domain_scores_gemma":[0.9984201,0.0002035324,0.0008356575,0.0002635565,0.00009542341,0.0001816924],"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":[0.00003662301,0.000006379561,0.0007546009,0.00004826946,0.0006516394,0.0001104862,0.00173861,0.5774868,0.09911285,0.000001088449,0.0004333259,0.3196193],"study_design_scores_gemma":[0.0003433011,0.00005809423,0.008715612,0.0001341699,0.001099246,0.000006337935,0.0009668121,0.9677695,0.020345,0.0003983554,0.00002526415,0.0001383264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6154482,0.00002118814,0.3840563,0.0001309519,0.0001059704,0.000123037,0.00005117446,0.000004262712,0.00005889517],"genre_scores_gemma":[0.7584292,0.00002691453,0.241409,0.00003539415,0.00001291962,4.131873e-9,0.00002478575,0.00001525847,0.00004648352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3902827,"threshold_uncertainty_score":0.9308168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115015157505923,"score_gpt":0.2612037356853786,"score_spread":0.2400535841103194,"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."}}