{"id":"W3128963373","doi":"10.3390/atmos13050757","title":"Knowledge-Enhanced Deep Learning for Simulation of Extratropical Cyclone Wind Risk","year":2022,"lang":"en","type":"article","venue":"Atmosphere","topic":"Tropical and Extratropical Cyclones Research","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Division of Civil, Mechanical and Manufacturing Innovation; National Science Foundation","keywords":"Extratropical cyclone; Meteorology; Wind speed; Wind direction; Weather Research and Forecasting Model; Tropical cyclone; Environmental science; Cyclone (programming language); Computer science; Geology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0005945876,0.0008633618,0.0006537134,0.0003756321,0.0002950263,0.0006982224,0.0009360228,0.001406747,0.001543196],"category_scores_gemma":[0.001762047,0.0004217397,0.0006497843,0.0003614403,0.0006136757,0.0005488053,0.000977349,0.001455836,0.0001557218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009229818,"about_ca_system_score_gemma":0.001336142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02476568,"about_ca_topic_score_gemma":0.01606575,"domain_scores_codex":[0.9998511,0.00004173357,0.00001025221,0.00003074755,0.00002985332,0.00003638511],"domain_scores_gemma":[0.9994312,0.0003791575,0.00004979318,0.00002005401,0.00008587079,0.00003389288],"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":[0.00001220611,0.00001396046,0.0004874358,0.0000103237,0.000006946559,0.00001948677,0.000006634695,0.9966792,0.0001272223,0.000417498,0.0001356981,0.002083483],"study_design_scores_gemma":[0.000001239933,0.000001895402,0.00003143934,8.849493e-7,6.584298e-7,6.338558e-7,9.012002e-7,0.9997551,0.00003458753,0.0001501261,0.00002196442,5.020179e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4311738,0.001618489,0.5522125,0.001381386,0.0001901418,0.000136375,0.0008043954,0.001255709,0.01122722],"genre_scores_gemma":[0.972115,0.0002005314,0.02513315,0.0001282499,0.00002178925,0.0001348348,0.0004121081,0.00002716513,0.001827207],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02476568,"threshold_uncertainty_score":0.04924303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01682718520830306,"score_gpt":0.2648439162660588,"score_spread":0.2480167310577557,"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."}}