{"id":"W4380590065","doi":"10.4271/2023-01-1377","title":"NRC’s ICE-MACR 2018-2023: What Has Been Learned So Far","year":2023,"lang":"en","type":"article","venue":"SAE International Journal of Advances and Current Practices in Mobility","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Icing; Turbofan; Gas compressor; Engineering; Ice crystals; Meteorology; Aerospace engineering; Environmental science; Icing conditions; Casing; Geology; Mechanical engineering; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001089407,0.0001359702,0.0002139118,0.0002701353,0.00006412879,0.0003157926,0.0003906493,0.00006306842,0.00002163233],"category_scores_gemma":[0.001166073,0.0001180142,0.00006938944,0.0002181532,0.0001324742,0.002428905,0.0001114502,0.0005592327,0.00001627868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001257072,"about_ca_system_score_gemma":0.0000480822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002840801,"about_ca_topic_score_gemma":0.0001607008,"domain_scores_codex":[0.9986374,0.00004997243,0.0004730513,0.0001688484,0.0004830555,0.0001877223],"domain_scores_gemma":[0.9987758,0.0003894209,0.0004280991,0.0001418242,0.0002199631,0.00004489202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009850291,0.0001006098,0.008362324,0.0001156746,0.00007810277,0.00004440376,0.000462874,0.0196596,0.0002273132,0.0001666188,0.0008280344,0.969856],"study_design_scores_gemma":[0.001391655,0.0002661508,0.04023051,0.001007546,0.00005611402,0.0001814541,0.005466691,0.01202189,0.001938175,0.02237454,0.9146414,0.0004238854],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.947847,0.03866227,0.001587426,0.003245165,0.007911494,0.0001325825,0.0000148256,0.0002232467,0.0003759682],"genre_scores_gemma":[0.8803625,0.1189263,0.000444324,0.00002195919,0.0002043457,0.000005362439,0.000004214494,0.00001055543,0.00002051276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9694321,"threshold_uncertainty_score":0.4812479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05752955072051937,"score_gpt":0.3715420065576685,"score_spread":0.3140124558371492,"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."}}