{"id":"W634606735","doi":"10.1016/j.ijheatfluidflow.2015.05.012","title":"Aero-thermal optimization of in-flight electro-thermal ice protection systems in transient de-icing mode","year":2015,"lang":"en","type":"article","venue":"International Journal of Heat and Fluid Flow","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":97,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Icing; Aerodynamics; Transient (computer programming); Computer science; Thermal energy; Energy consumption; Icing conditions; Aerodynamic heating; Simulation; Automotive engineering; Heat transfer; Aerospace engineering; Mechanics; Meteorology; Engineering; Physics; Thermodynamics","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":[0.0002488222,0.0006899813,0.0007224993,0.000366737,0.0006373467,0.000938331,0.0003518981,0.0007547016,0.003586023],"category_scores_gemma":[0.0004443969,0.0003318688,0.0005418629,0.0001750652,0.0003283222,0.0003319802,0.0004385377,0.0004505266,0.0002553797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005044845,"about_ca_system_score_gemma":0.0007970367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009592685,"about_ca_topic_score_gemma":0.007061522,"domain_scores_codex":[0.9998844,0.00002331131,0.000003765869,0.00001635204,0.00002079519,0.00005144313],"domain_scores_gemma":[0.9998127,0.00008345783,0.00002809369,0.000007605936,0.00004516042,0.00002297138],"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":[0.0001190217,0.00004707725,0.0005030938,0.0000399014,0.00001777296,0.00006500175,0.00002217694,0.9897699,0.005798968,0.0002595029,0.0001882329,0.003169315],"study_design_scores_gemma":[0.00001853968,0.0001768806,0.0008533515,0.000004512654,0.00001632662,0.00001011954,0.00003919485,0.9969615,0.001626933,0.00009412684,0.0001941625,0.000004390941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8885134,0.000478439,0.07908446,0.0003614665,0.00009923516,0.0001222689,0.000222178,0.0002681251,0.0308504],"genre_scores_gemma":[0.9972911,0.00004328381,0.001195985,0.00001386696,0.000004438781,0.00001912014,0.00003071812,0.00001201976,0.001389443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009592685,"threshold_uncertainty_score":0.01907367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01139888488775682,"score_gpt":0.2241946073774012,"score_spread":0.2127957224896443,"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."}}