{"id":"W2975025647","doi":"10.1080/07038992.2019.1662284","title":"Synergistic RADARSAT-2 and Sentinel-1 SAR Images for Ocean Feature Analysis","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; University of Waterloo","funders":"","keywords":"Remote sensing; Synthetic aperture radar; Feature (linguistics); Geography; Radar imaging; Cartography; Meteorology; Computer science; Radar; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000205905,0.00007604393,0.0001509088,0.0001716012,0.0001223945,0.00005692268,0.00004620512,0.00004699659,0.00008548612],"category_scores_gemma":[0.00007593638,0.00007076298,0.000100421,0.0002656429,0.00006707256,0.0001094136,0.000006543763,0.0001048742,0.0000100728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001370901,"about_ca_system_score_gemma":0.00004623121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003448805,"about_ca_topic_score_gemma":0.006292335,"domain_scores_codex":[0.9994483,0.00002417067,0.0001389348,0.0001144158,0.0001016247,0.0001725659],"domain_scores_gemma":[0.9994276,0.00002865127,0.0001344233,0.00008590532,0.00003245999,0.00029098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003949798,0.000004176184,0.04184573,0.00004412609,0.0003800176,0.0001783188,0.0008158705,0.002822279,0.03467964,0.00001281815,0.02052972,0.8986478],"study_design_scores_gemma":[0.002244557,0.0002671088,0.2540373,0.0002288001,0.001647056,0.0009825532,0.001249538,0.1608354,0.02281812,0.001359012,0.5534233,0.0009073307],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820092,0.0001004963,0.01520121,0.001000588,0.0002387506,0.00007014802,0.000005091462,0.000004213737,0.001370276],"genre_scores_gemma":[0.9690818,0.000008063513,0.02954707,0.0002901066,0.00006348067,7.246416e-10,0.000002465756,0.00000918323,0.0009978664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8977405,"threshold_uncertainty_score":0.5213584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0048975942736552,"score_gpt":0.197012202619684,"score_spread":0.1921146083460288,"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."}}