{"id":"W3216951913","doi":"","title":"Earthquake Early Warning (EEW) End-user Education and Training at Ocean Networks Canada","year":2020,"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":"Training (meteorology); Warning system; Earthquake warning system; Computer science; Meteorology; Telecommunications; Geography","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":[0.0009075255,0.0002499557,0.0001662771,0.0007021366,0.003171546,0.001372144,0.0007159239,0.0008461472,0.06704245],"category_scores_gemma":[0.00170638,0.0002989019,0.0001086633,0.0004509625,0.0004393269,0.0003699712,0.001086926,0.001007516,0.01082827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01039567,"about_ca_system_score_gemma":0.07168865,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9215769,"about_ca_topic_score_gemma":0.9695494,"domain_scores_codex":[0.9993249,0.00005566346,0.000008961524,0.00005429805,0.0002174614,0.0003388002],"domain_scores_gemma":[0.9937438,0.0001787247,0.00005623681,0.00008610557,0.002037955,0.00389712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002995088,0.0009051402,0.05272806,0.00005306103,0.000006610669,0.0003756107,0.00192562,0.001116495,0.003031743,0.001404488,0.7684387,0.1697149],"study_design_scores_gemma":[0.0001190685,0.000205398,0.2072675,0.0001098256,0.000007779456,0.00008425273,0.00714042,0.005954875,0.002215468,0.0005824493,0.7762653,0.00004771624],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2987362,0.0004607172,0.0051586,0.05697089,0.001584608,0.001060945,0.01674273,0.003381768,0.6159035],"genre_scores_gemma":[0.2074017,0.0003771724,0.003281062,0.002044894,0.00009300419,0.0001208591,0.002736704,0.0002624486,0.783682],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07842308,"threshold_uncertainty_score":0.2242793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01710596312221696,"score_gpt":0.2125434631382831,"score_spread":0.1954375000160662,"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."}}