{"id":"W1982063030","doi":"10.3137/ao.420102","title":"A radar‐based methodology for preparing a severe thunderstorm climatology in central Alberta","year":2004,"lang":"en","type":"article","venue":"ATMOSPHERE-OCEAN","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Alberta","funders":"","keywords":"Thunderstorm; Meteorology; Climatology; Radar; Weather radar; Environmental science; Remote sensing; Geography; Computer science; Geology; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003876569,0.0001815643,0.0003596724,0.000012012,0.0001555795,0.0000264666,0.0002409016,0.0001688694,0.001019758],"category_scores_gemma":[0.0002889408,0.0001518117,0.0001126898,0.0002168323,0.00009996847,0.000135351,0.00001353928,0.0001596686,0.00004008973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002789752,"about_ca_system_score_gemma":0.0001183043,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006156093,"about_ca_topic_score_gemma":0.03496147,"domain_scores_codex":[0.9982694,0.0001849124,0.0003554384,0.0004102511,0.0001164488,0.0006635082],"domain_scores_gemma":[0.9980423,0.001447559,0.00009546016,0.0002257609,0.00002169135,0.0001672243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003406803,0.00006521894,0.6249795,0.00003053367,0.0000290209,0.00001087239,0.0006650771,0.3653721,0.000007381663,0.005604577,0.0001987122,0.002696292],"study_design_scores_gemma":[0.008914844,0.001400205,0.6630893,0.00004665606,0.00009724171,0.00006314884,0.001036057,0.1229664,0.00007753489,0.187933,0.01334415,0.001031427],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775515,0.0001809463,0.007341649,0.0007492185,0.000295078,0.0005039577,0.00002196654,0.00005311169,0.01330262],"genre_scores_gemma":[0.9472322,0.000005494612,0.0515387,0.0009326281,0.00005430033,0.000001947916,0.0001011569,0.000006682124,0.000126854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2424057,"threshold_uncertainty_score":0.9998934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04706911704054132,"score_gpt":0.2689043820945586,"score_spread":0.2218352650540173,"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."}}