{"id":"W4380589950","doi":"10.4271/2023-01-1418","title":"Comparison of Freeze-Out versus Grind-Out Ice Crystals for Generating Ice Accretion Using the ICE-MACR","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":"Transport Canada; National Research Council Canada","funders":"","keywords":"Icing; Ice crystals; Span (engineering); Meteorology; Grind; Materials science; Altitude (triangle); Accretion (finance); Atmospheric sciences; Geology; Engineering; Physics; Geometry; Composite material; Mathematics; Astrophysics; Grinding; Structural engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001007461,0.0002701524,0.000357823,0.0004948711,0.0002826583,0.0006545547,0.0007032335,0.0003361805,0.002417142],"category_scores_gemma":[0.001413811,0.000201763,0.0004790266,0.0003575527,0.000257749,0.0005015956,0.0003443735,0.0004998932,0.0007797676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003266095,"about_ca_system_score_gemma":0.0003565372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001199577,"about_ca_topic_score_gemma":0.001962489,"domain_scores_codex":[0.999506,0.00003866926,0.00004157875,0.00006411764,0.0002885273,0.00006105802],"domain_scores_gemma":[0.9992393,0.000231817,0.00008078899,0.00013446,0.0002362693,0.00007746836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001291631,0.0005536104,0.004191198,0.000671623,0.00005764972,0.0003605472,0.0002886896,0.01711493,0.9200373,0.001116615,0.001588503,0.05272768],"study_design_scores_gemma":[0.00009113119,0.001690943,0.01047554,0.00002773485,0.00005077186,0.0001810866,0.0001149911,0.04239151,0.9383547,0.00009094115,0.006493655,0.00003694453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.962,0.0008899475,0.02297984,0.0001158312,0.0001702143,0.000358742,0.0009363831,0.001201035,0.01134794],"genre_scores_gemma":[0.9499456,0.0006112914,0.04459655,0.00008168902,0.00002377408,0.0001732587,0.001168024,0.0004908662,0.00290895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002417142,"threshold_uncertainty_score":0.008086145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1221282289332882,"score_gpt":0.4511343816354119,"score_spread":0.3290061527021236,"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."}}