{"id":"W2921742767","doi":"10.1175/waf-d-18-0037.1","title":"Aircraft Icing Study Using Integrated Observations and Model Data","year":2019,"lang":"en","type":"article","venue":"Weather and Forecasting","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; Barrie Urology Group; Environment and Climate Change Canada","funders":"Ministère de la Défense Nationale; Environment and Climate Change Canada","keywords":"Icing; Meteorology; Environmental science; Radiosonde; Ceilometer; Airspeed; Icing conditions; Radiometer; Climatology; Atmospheric sciences; Remote sensing; Aerosol; Engineering; Aerospace engineering; Geography; Geology","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":[0.0006435031,0.0006573394,0.0004682955,0.001032391,0.0003345075,0.0008813764,0.000530256,0.000574321,0.000510041],"category_scores_gemma":[0.001214012,0.0002828214,0.0008092526,0.001001219,0.000190545,0.0005634199,0.0002988307,0.0006485435,0.0001811422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001412691,"about_ca_system_score_gemma":0.001093882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.258539,"about_ca_topic_score_gemma":0.164824,"domain_scores_codex":[0.9997067,0.00004162289,0.00002216687,0.0001101501,0.00006787156,0.00005144006],"domain_scores_gemma":[0.9993374,0.0001934408,0.0001021466,0.00007768207,0.0002196801,0.00006971643],"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":[0.0007672139,0.001276984,0.4115113,0.0001547677,0.0006035418,0.0004732182,0.0002069591,0.5488533,0.007191012,0.000236728,0.001972537,0.02675244],"study_design_scores_gemma":[0.00005118313,0.0002025672,0.2136023,0.00001087289,0.00008562509,0.00003586343,0.0001726545,0.783668,0.001705834,0.00004021477,0.0003921919,0.00003269382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976299,0.00004427537,0.000741647,0.00002599337,0.00001044145,0.00001842306,0.0009860244,0.0001040147,0.0004392728],"genre_scores_gemma":[0.9958106,0.00003523423,0.001312002,0.000007132938,0.000007681033,0.00001030529,0.002680108,0.000007723209,0.0001291753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.258539,"threshold_uncertainty_score":0.5140683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.129539121231719,"score_gpt":0.2636204941603821,"score_spread":0.1340813729286631,"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."}}