{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002033602,0.00008528736,0.0001338463,0.00007818265,0.0001887493,0.00003883406,0.0007407124,0.0001435492,0.00008577667],"category_scores_gemma":[0.0003822079,0.00006934247,0.00004147812,0.0004981236,0.00009190057,0.0001271104,0.0000269944,0.0005433851,0.00003129352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007258911,"about_ca_system_score_gemma":0.00006002805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002539093,"about_ca_topic_score_gemma":0.0100172,"domain_scores_codex":[0.9992247,0.0001094337,0.0001963798,0.000153159,0.0001270671,0.0001892357],"domain_scores_gemma":[0.9980745,0.001039441,0.00006647838,0.0006073417,0.00008092207,0.0001313049],"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":[0.00003692496,0.00007234726,0.4805635,0.000004765251,0.00001179895,5.249885e-7,0.001193646,0.4851505,1.880304e-7,0.01384557,0.0007352576,0.01838497],"study_design_scores_gemma":[0.0001627189,0.00007460092,0.03648862,0.000007866153,0.00000855589,3.89292e-7,0.0003019286,0.8345862,1.917681e-7,0.05954709,0.06868399,0.0001378341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3054095,0.0429392,0.5854923,0.0161299,0.001384801,0.00218701,0.001185536,0.0003228319,0.04494894],"genre_scores_gemma":[0.8525885,0.0001227447,0.146345,0.0005044269,0.00004328946,0.000009470236,0.0003716509,0.000001810744,0.0000130691],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.547179,"threshold_uncertainty_score":0.5589833,"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."}}