{"id":"W2785118221","doi":"","title":"Using Tornado, Lightning, and Population Data to Identify Tornado Prone Areas in Canada","year":2012,"lang":"en","type":"article","venue":"26th Conference on Severe Local Storms (5 - 8 November 2012)","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Tornado; Lightning (connector); Meteorology; Population; Geography; Medicine; Environmental health","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003813025,0.0002245208,0.0002911527,0.00008549877,0.0001559899,0.00007638185,0.000342275,0.00009849347,0.004214193],"category_scores_gemma":[0.00007680878,0.0001730207,0.00001743003,0.0002183003,0.00004009501,0.0008766682,0.00007909591,0.0002273208,0.0001007075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001215213,"about_ca_system_score_gemma":0.0002222196,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8408915,"about_ca_topic_score_gemma":0.9469618,"domain_scores_codex":[0.9981084,0.0000934224,0.000346162,0.0004346291,0.0004352485,0.000582104],"domain_scores_gemma":[0.9988071,0.0001212217,0.0001036512,0.0004323674,0.00004366543,0.0004919426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007178338,0.00003388952,0.9593107,0.00001314448,0.00001204635,0.000005815619,0.0001326826,0.005705138,0.00003041524,0.0005784213,0.000624522,0.03348142],"study_design_scores_gemma":[0.0002638558,0.00005683722,0.9644248,0.00003499835,0.00001230999,0.000005992858,0.000122205,0.03110921,0.000004518978,0.0003925184,0.003286508,0.0002862626],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919852,0.0002235337,0.0009254662,0.0002012827,0.0005228161,0.0003253203,0.0001827287,0.00001919839,0.005614479],"genre_scores_gemma":[0.9980894,0.000006118787,0.0006290104,0.0006390117,0.000155615,0.000001877901,0.0002460127,0.000006646054,0.0002263128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1060703,"threshold_uncertainty_score":0.9966961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1165786907856661,"score_gpt":0.3028569058667115,"score_spread":0.1862782150810454,"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."}}