{"id":"W2131340082","doi":"10.1109/igarss.2008.4779078","title":"Wind Speed Retrievals from Multi-Sensor Satellite Data from Hurricanes and Tropical Cyclones","year":2008,"lang":"en","type":"article","venue":"","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography","funders":"National Natural Science Foundation of China; Canadian Space Agency; Chinese Academy of Sciences; National Science Foundation","keywords":"Typhoon; Tropical cyclone; Meteorology; Wind speed; Radiometer; Environmental science; Remote sensing; Satellite; Numerical weather prediction; Microwave radiometer; Microwave; Weather forecasting; Computer science; Geology; Geography; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003449408,0.0004821366,0.0004807135,0.0008599734,0.0002893161,0.0004391088,0.0004297669,0.0003511879,0.0008672436],"category_scores_gemma":[0.001224166,0.000330862,0.0004010102,0.0007126858,0.00009357915,0.0006713467,0.0003037491,0.0003289516,0.0003473266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002603358,"about_ca_system_score_gemma":0.0004451823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005087154,"about_ca_topic_score_gemma":0.006087658,"domain_scores_codex":[0.9998373,0.00002335645,0.00001634001,0.00003624314,0.00006702667,0.00001977848],"domain_scores_gemma":[0.9997494,0.00004970307,0.00005044685,0.00004154784,0.00008935732,0.00001961172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002495859,0.0002207816,0.03917206,0.0002121024,0.0001601227,0.0002185609,0.000100227,0.272783,0.09371583,0.001715514,0.004467584,0.5869847],"study_design_scores_gemma":[0.0001078531,0.00008656805,0.03467214,0.00001413973,0.00002838743,0.0000812049,0.00003123242,0.9352834,0.02677937,0.0005912011,0.002284548,0.00004004918],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5997242,0.0005465429,0.3918087,0.0001727761,0.0002099464,0.0002011505,0.001567776,0.003102616,0.002666231],"genre_scores_gemma":[0.593849,0.0002369364,0.4014577,0.00003127022,0.00009581689,0.0001363799,0.002424587,0.0001586857,0.00160969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005087154,"threshold_uncertainty_score":0.01011509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.127693748026944,"score_gpt":0.2747907548541898,"score_spread":0.1470970068272458,"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."}}