{"id":"W2010058194","doi":"10.1038/ncomms7599","title":"A Bayesian modelling framework for tornado occurrences in North America","year":2015,"lang":"en","type":"article","venue":"Nature Communications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Development Research Centre; Environment and Climate Change Canada; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tornado; Bayesian probability; Computer science; Geography; Meteorology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00269692,0.0006589976,0.0009323437,0.001462027,0.0009204855,0.002137333,0.002031791,0.001495252,0.003633724],"category_scores_gemma":[0.008276375,0.0008903994,0.001332586,0.001350606,0.001042286,0.001869057,0.001166905,0.001487636,0.0003479633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002046168,"about_ca_system_score_gemma":0.001871421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09988354,"about_ca_topic_score_gemma":0.08906731,"domain_scores_codex":[0.9992117,0.0004368949,0.00003615213,0.0001500323,0.00009659564,0.00006853171],"domain_scores_gemma":[0.9976284,0.001684207,0.0002859285,0.00007256938,0.0002398535,0.00008912219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002516588,0.00001617853,0.002168642,0.00002224578,0.00006618241,0.00007300805,0.0001551638,0.9345161,0.0001571872,0.05595122,0.0006568798,0.006192055],"study_design_scores_gemma":[0.000008250965,0.000006637213,0.0004904957,0.000009272431,0.00001167948,0.00001972426,0.00003380029,0.9713605,0.00001892294,0.02732187,0.0007060657,0.00001276539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05807041,0.0005349901,0.9332446,0.001373829,0.00005444231,0.00006440427,0.0008069801,0.0002864432,0.005563887],"genre_scores_gemma":[0.8254402,0.001379393,0.1624406,0.0002014366,0.0001470883,0.00042103,0.001107671,0.000113128,0.008749433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09988354,"threshold_uncertainty_score":0.1986043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08770512850694566,"score_gpt":0.3124169589833769,"score_spread":0.2247118304764312,"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."}}