{"id":"W3084056345","doi":"","title":"Development of new tsunami detection algorithms for high frequency radars and application to tsunami warning in British Columbia, Canada","year":2016,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Warning system; Remote sensing; Algorithm; Radar; Geology; Computer science; Meteorology; Seismology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004350293,0.00008194991,0.0001668835,0.00004178335,0.0001872107,0.00004635652,0.00018961,0.00006205183,2.629939e-7],"category_scores_gemma":[0.0002872292,0.0001054869,0.00001334705,0.0001470174,0.00002318244,0.0001311294,0.00006927803,0.00006235187,0.00000136428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001090187,"about_ca_system_score_gemma":0.0003043666,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9394627,"about_ca_topic_score_gemma":0.9957302,"domain_scores_codex":[0.9988508,0.00002233116,0.0003573338,0.0003489658,0.0001488002,0.0002717762],"domain_scores_gemma":[0.999307,0.0002359596,0.0001519601,0.000138293,0.00007871144,0.00008807068],"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":[0.000002944159,0.0000141705,0.06049328,0.00002276801,0.00001633844,0.000006625797,0.0006664821,0.000139799,0.002361573,0.00001745705,0.0001145867,0.936144],"study_design_scores_gemma":[0.00043965,0.00003982147,0.9942812,0.0001707648,0.000003879847,0.00001223258,0.00009540516,0.0002191502,0.002525527,0.0007886012,0.001245018,0.0001787118],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9000545,0.00008510824,0.09895058,0.0003895095,0.0001839946,0.0002400998,0.000002413966,0.0000337129,0.000060056],"genre_scores_gemma":[0.8929459,0.000008319385,0.1067653,0.0001139514,0.00003157292,0.0000381052,0.000001437968,0.000006375298,0.00008909289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9359652,"threshold_uncertainty_score":0.4301633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049687417094095,"score_gpt":0.2137141424463609,"score_spread":0.2032172682754199,"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."}}