{"id":"W3020766178","doi":"10.5194/gmd-13-1975-2020","title":"The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory","year":2020,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Biological and Environmental Research; Office of Science; U.S. Department of Energy","keywords":"Cloud computing; Remote sensing; Lidar; Radar; Computer science; Meteorology; Sampling (signal processing); Environmental science; Geography","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":[0.001318822,0.0009905031,0.000533887,0.0005155356,0.0003937326,0.001199256,0.002794031,0.0007505028,0.004009722],"category_scores_gemma":[0.002365692,0.0005969566,0.0007973387,0.0007777802,0.0004058505,0.001021175,0.0009939361,0.001500324,0.001162916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006829932,"about_ca_system_score_gemma":0.001563563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01208004,"about_ca_topic_score_gemma":0.008907607,"domain_scores_codex":[0.9995333,0.0001193975,0.00003837576,0.00006157921,0.0001870254,0.00006031426],"domain_scores_gemma":[0.99897,0.0003056882,0.00009021963,0.0002449306,0.0002539759,0.0001350538],"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":[0.0003165175,0.0002128959,0.007442664,0.0002081422,0.0002214861,0.0002193873,0.0001460868,0.9198983,0.007976315,0.01264407,0.02455831,0.02615581],"study_design_scores_gemma":[0.00009850867,0.00003098096,0.0003546032,0.000008573388,0.00001299033,0.00002131885,0.000009701052,0.9861011,0.002305746,0.001226964,0.009812519,0.0000170496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1685105,0.0008648467,0.6777927,0.001185516,0.0005935756,0.001295081,0.02384439,0.07935929,0.04655413],"genre_scores_gemma":[0.6570321,0.0006513133,0.3050697,0.0004480355,0.0001175698,0.0009517018,0.02333199,0.007603579,0.004794061],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01208004,"threshold_uncertainty_score":0.02401948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04570921190194439,"score_gpt":0.2095586722781578,"score_spread":0.1638494603762134,"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."}}