{"id":"W4405907029","doi":"10.1109/icjece.2024.3506115","title":"Ship Wake Detection Based on Polarimetric Enhancement and Deep Learning via a Simulated Full-Polarized Dataset","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Polarimetry; Wake; Humanities; Computer science; Physics; Philosophy; Optics; Mechanics","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":[0.0001680312,0.0001057046,0.0001355093,0.0005144884,0.0001017036,0.0001846697,0.00004924825,0.00005318083,0.00002708903],"category_scores_gemma":[0.00003062214,0.00008471078,0.00003257988,0.0004086424,0.00001231517,0.00008855292,0.000002488402,0.0003893115,0.000002844146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001842594,"about_ca_system_score_gemma":0.00005899604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001315228,"about_ca_topic_score_gemma":0.0005312827,"domain_scores_codex":[0.9993299,0.00002837611,0.000167505,0.0001281312,0.0001020296,0.0002440793],"domain_scores_gemma":[0.9993519,0.0001834617,0.00002899337,0.00003795245,0.00001908148,0.0003786727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004026763,0.000004936049,0.001614891,0.00005354465,0.00006716107,0.0004747596,0.00006530364,0.2513458,0.001012956,0.000008106772,0.00002462956,0.7452876],"study_design_scores_gemma":[0.0001605813,0.0005516177,0.01077563,0.00005798268,0.00002023308,0.0002225518,0.000001291196,0.9848081,0.00009643284,0.00001201822,0.003187242,0.0001062413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6198228,0.008285635,0.3708839,0.0001401128,0.000714382,0.00008600855,0.00001793581,0.00002529888,0.000023934],"genre_scores_gemma":[0.9983271,0.00003060956,0.001332121,0.00008077325,0.0001955951,2.302088e-9,0.00002541624,0.000004648223,0.000003760239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7451814,"threshold_uncertainty_score":0.3454405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004603290886286904,"score_gpt":0.1656699555031464,"score_spread":0.1610666646168595,"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."}}