{"id":"W1563259566","doi":"10.1109/radar.2015.7131248","title":"Oil slick drift prediction using commercial X-band radar","year":2015,"lang":"en","type":"article","venue":"","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Rutter (Canada)","funders":"","keywords":"Radar; Trajectory; Current (fluid); Monte Carlo method; Remote sensing; Meteorology; Geology; Computer science; Geodesy; Geography; Physics; Telecommunications; Statistics; Mathematics","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":[0.0002202356,0.0003233998,0.0002008107,0.0002680319,0.0001933584,0.000228009,0.0002727097,0.0001968591,0.0003912048],"category_scores_gemma":[0.0004493054,0.0001054729,0.0001564975,0.0002338012,0.0001174987,0.0002525917,0.0001329265,0.0001740117,0.00009952292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006074153,"about_ca_system_score_gemma":0.0008511645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06914821,"about_ca_topic_score_gemma":0.0629845,"domain_scores_codex":[0.9999324,0.00001062033,0.000003747349,0.00001847469,0.00001889618,0.0000158803],"domain_scores_gemma":[0.9998112,0.00004689373,0.00003405204,0.00001388865,0.00007473727,0.00001916025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004214652,0.0001225344,0.1049192,0.00004161353,0.0000467411,0.0001856517,0.00004564489,0.8321759,0.02404437,0.0002417721,0.0005966377,0.03715831],"study_design_scores_gemma":[0.00001680367,0.00003126158,0.01423873,0.000001574912,0.000005541148,0.000010062,0.000009500308,0.9826859,0.002914309,0.00002406194,0.00005800074,0.000004276623],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908778,0.00003988744,0.008071974,0.00002532379,0.000007847323,0.000009289611,0.0001565653,0.0001644912,0.0006469364],"genre_scores_gemma":[0.9959707,0.00002367501,0.003615968,0.000003414885,0.000001541611,0.000003062079,0.0001624979,0.000005056214,0.0002141232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06914821,"threshold_uncertainty_score":0.1374915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04889994615256534,"score_gpt":0.2280581232855126,"score_spread":0.1791581771329472,"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."}}