{"id":"W2923568062","doi":"10.5194/amt-12-4591-2019","title":"Development and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm","year":2019,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Leibniz-Institut für Troposphärenforschung; Leibniz-Gemeinschaft; Office of Science; Biological and Environmental Research; European Commission; Deutsche Forschungsgemeinschaft; U.S. Department of Energy","keywords":"Algorithm; Radar; Doppler effect; Doppler radar; Zenith; Remote sensing; Computer science; Smoothing; Spectral line; Cloud computing; Meteorology; Environmental science; Geology; Physics; Computer vision","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":[0.003373355,0.001029931,0.001043745,0.001113527,0.0006121682,0.0008538244,0.001993296,0.001486959,0.001599098],"category_scores_gemma":[0.006854047,0.0003548387,0.0006244034,0.000745927,0.0004018327,0.0009408407,0.0007799802,0.00118138,0.0007877834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007838308,"about_ca_system_score_gemma":0.001879399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005100571,"about_ca_topic_score_gemma":0.002956914,"domain_scores_codex":[0.9987066,0.0003797509,0.0001026438,0.0004593992,0.0002580264,0.0000936144],"domain_scores_gemma":[0.9947825,0.002655284,0.0002848356,0.0003291464,0.00182579,0.0001224831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000339758,0.000592677,0.00723428,0.0002003009,0.0001962357,0.0001034574,0.00007322278,0.2838944,0.01330431,0.001138892,0.003296399,0.6896261],"study_design_scores_gemma":[0.00001638992,0.00004168051,0.0004312577,0.000004032167,0.00000660229,0.0000143291,0.000007361075,0.9963551,0.00271522,0.000179341,0.0002247741,0.00000402349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1239858,0.00051451,0.8667549,0.0001679738,0.0001327679,0.000340742,0.0002720827,0.006237401,0.00159376],"genre_scores_gemma":[0.4127283,0.00009109987,0.5839998,0.0001459609,0.00003967807,0.0003562189,0.001073583,0.0001508241,0.00141463],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005100571,"threshold_uncertainty_score":0.01784021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01818093698511782,"score_gpt":0.2154625447770543,"score_spread":0.1972816077919365,"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."}}