{"id":"W4319442274","doi":"10.5194/egusphere-2023-120","title":"The Canadian Atmospheric Model version 5 (CanAM5.0.3)","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Langley Research Center; National Aeronautics and Space Administration","keywords":"Environmental science; Climate model; Radiative transfer; Climatology; Atmospheric sciences; Precipitation; Atmosphere (unit); Cloud fraction; Atmospheric models; Amazonian; Aerosol; Water cycle; Atmospheric model; Meteorology; Climate change; Cloud computing; Cloud cover; Geography; Geology; Amazon rainforest; Physics; Computer science","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":[0.001345965,0.001497276,0.001203429,0.001832832,0.001574287,0.00294383,0.003418276,0.001439342,0.0295485],"category_scores_gemma":[0.002858133,0.0006953945,0.001648082,0.007042093,0.0004460085,0.001779248,0.0009144224,0.002486859,0.01198013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00755761,"about_ca_system_score_gemma":0.01877209,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9203942,"about_ca_topic_score_gemma":0.8715038,"domain_scores_codex":[0.999052,0.0001067806,0.00004080654,0.0001309559,0.0005291762,0.0001403326],"domain_scores_gemma":[0.9979977,0.00008203997,0.00006798966,0.0001610361,0.001530059,0.0001612136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001810284,0.00004751116,0.00470478,0.0005755886,0.000390952,0.0001088311,0.0001038993,0.03060416,0.001255095,0.01151952,0.9201229,0.03038569],"study_design_scores_gemma":[0.0003241364,0.000017694,0.01274167,0.0001917262,0.0001833024,0.00004287241,0.00009847868,0.04805375,0.001224043,0.005612771,0.9313636,0.0001458858],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.005414912,0.002868087,0.02225507,0.002152256,0.0009468776,0.0004387227,0.8919282,0.01530158,0.05869429],"genre_scores_gemma":[0.06688499,0.003593582,0.0583123,0.001023358,0.0002749665,0.00085368,0.8384768,0.005276559,0.02530368],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.07960582,"threshold_uncertainty_score":0.1601492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126792060510192,"score_gpt":0.2035803372266964,"score_spread":0.1909011311756773,"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."}}