{"id":"W2010410731","doi":"10.1175/2009jtecha1284.1","title":"A Methodology to Derive Radar Reflectivity–Liquid Equivalent Snow Rate Relations Using C-Band Radar and a 2D Video Disdrometer","year":2009,"lang":"en","type":"article","venue":"Journal of Atmospheric and Oceanic Technology","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Aeronautics and Space Administration","keywords":"Disdrometer; Snow; Radar; Power law; Environmental science; Remote sensing; Meteorology; Geology; Mathematics; Physics; Computer science; Statistics","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":[0.0009435606,0.0001561181,0.000427239,0.00009382886,0.0001910867,0.00003719238,0.0001518743,0.0001438171,0.0002187537],"category_scores_gemma":[0.0004424303,0.0001230615,0.00007837194,0.0007432703,0.0001135499,0.0002630394,0.00001583734,0.0002643234,0.000004525299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001965213,"about_ca_system_score_gemma":0.00006878763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002232945,"about_ca_topic_score_gemma":0.00005376856,"domain_scores_codex":[0.9986919,0.000219181,0.0004290483,0.0002246123,0.0001737009,0.0002615933],"domain_scores_gemma":[0.9990529,0.0002462399,0.0003212844,0.0001236722,0.0001105817,0.000145352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002569819,0.0002421704,0.2306764,0.00005733692,0.001265243,0.0003834048,0.002768431,0.004107485,0.1673012,0.001537291,0.001504295,0.5875869],"study_design_scores_gemma":[0.005196885,0.01523974,0.8740883,0.0004374025,0.001875943,0.002987432,0.004368772,0.01480205,0.01116087,0.06099021,0.007283131,0.001569243],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9225602,0.002825555,0.07087842,0.003369692,0.0001096316,0.00009288856,0.000002636511,0.00002407794,0.0001368637],"genre_scores_gemma":[0.8847781,0.0003332977,0.1144501,0.00033472,0.000050428,1.678238e-7,0.000001035934,0.000003553288,0.00004868136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6434119,"threshold_uncertainty_score":0.50183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0418292126744678,"score_gpt":0.2830070461496829,"score_spread":0.2411778334752151,"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."}}