{"id":"W4410359139","doi":"10.1109/radar58436.2024.10993981","title":"Differentiating Tsunamis from Atmospheric-Induced Events Using Coastal High-Frequency Radars","year":2024,"lang":"en","type":"article","venue":"","topic":"earthquake and tectonic studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Remote sensing; Radar; Meteorology; Geology; Computer science; Geography; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006105996,0.000283086,0.0001830553,0.001115526,0.0001618465,0.0006777882,0.0002231383,0.0004194265,0.0006444222],"category_scores_gemma":[0.002511911,0.0001206644,0.0001429298,0.0006408698,0.000171062,0.0004437006,0.0002989578,0.000223557,0.0002300849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001353603,"about_ca_system_score_gemma":0.000202629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003436155,"about_ca_topic_score_gemma":0.01345096,"domain_scores_codex":[0.9997548,0.00005826914,0.0000308704,0.00005113878,0.00005256593,0.00005227617],"domain_scores_gemma":[0.9987611,0.0004396205,0.0003150674,0.00009892284,0.0002742916,0.0001110905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006966445,0.0002077371,0.7625194,0.0001953876,0.00008960268,0.000727277,0.000615105,0.003167647,0.1030558,0.0003075113,0.0004577935,0.1279602],"study_design_scores_gemma":[0.0000335508,0.0002549835,0.9730235,0.00002630584,0.00006269562,0.0005633197,0.0006768696,0.0141737,0.01009026,0.0001480317,0.0009246723,0.00002205412],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934552,0.0002040735,0.004238416,0.00002488548,0.00001496943,0.00003087481,0.0002163898,0.00004417284,0.001771032],"genre_scores_gemma":[0.9910842,0.0002354198,0.007938016,0.00002174956,0.0000252896,0.00001230869,0.0003573371,0.000005681173,0.0003201089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003436155,"threshold_uncertainty_score":0.006832302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02265171675241964,"score_gpt":0.229485472561632,"score_spread":0.2068337558092123,"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."}}