{"id":"W4392615971","doi":"10.5194/egusphere-2024-594","title":"Effect of Secondary Ice Production Processes on the Simulation of ice pellets using the Predicted Particle Properties microphysics scheme","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; National Research Council Canada; Université du Québec à Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Pellets; Ice crystals; Clear ice; Ice nucleus; Precipitation; Environmental science; Atmospheric sciences; Freezing rain; Snow; Sea ice growth processes; Graupel; Supercooling; Meteorology; Arctic ice pack; Climatology; Geology; Antarctic sea ice; Sea ice; Physics; Nucleation; Thermodynamics","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":[0.000434777,0.0006165234,0.000444959,0.000229815,0.0005002698,0.0006543198,0.0008253952,0.0007295698,0.001224623],"category_scores_gemma":[0.001623222,0.0002771766,0.0005979753,0.0002647263,0.0005254048,0.0003936688,0.0004217254,0.0008199352,0.0001220719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009322282,"about_ca_system_score_gemma":0.001490045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0321116,"about_ca_topic_score_gemma":0.0136273,"domain_scores_codex":[0.9998395,0.00004312642,0.00000919885,0.00002444456,0.00003471557,0.00004903595],"domain_scores_gemma":[0.9990926,0.0004809072,0.00009971248,0.0000871946,0.0001533185,0.0000863684],"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":[0.0001362753,0.00009835039,0.00745843,0.00002746206,0.0000256385,0.0001109294,0.00004529261,0.983024,0.005312975,0.0009121872,0.0001752419,0.002673245],"study_design_scores_gemma":[0.00002637896,0.00004392087,0.001023896,0.000001958822,0.000004625921,0.000007539666,0.000009082855,0.9967764,0.001907592,0.00008031794,0.0001139797,0.000004364169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831333,0.00005025017,0.01161793,0.0001082606,0.00004126152,0.00007518049,0.0003756786,0.0002445501,0.004353587],"genre_scores_gemma":[0.9929652,0.00002682764,0.006332332,0.0000246375,0.000004640219,0.00003331406,0.0001560828,0.00003902646,0.0004179943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0321116,"threshold_uncertainty_score":0.06384933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02386125931455233,"score_gpt":0.2438741298429671,"score_spread":0.2200128705284148,"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."}}