{"id":"W3151387854","doi":"","title":"Using Cloud Radar to Retrieve Entrainment Rates in Stratocumulus Clouds","year":2020,"lang":"en","type":"article","venue":"","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Marine stratocumulus; Cloud computing; Entrainment (biomusicology); Meteorology; Environmental science; Cloud top; Atmospheric sciences; Computer science; Geology; Geography; Operating system","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":[0.0004588009,0.0004476255,0.000363863,0.001077439,0.0002038921,0.0007472852,0.0003798778,0.0004046109,0.0003304207],"category_scores_gemma":[0.0009350316,0.0002131331,0.0002649993,0.0006501482,0.0001006188,0.0006876722,0.0002608715,0.0002799261,0.0001758841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003737997,"about_ca_system_score_gemma":0.000328443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01782835,"about_ca_topic_score_gemma":0.01464054,"domain_scores_codex":[0.9998864,0.00001206854,0.000009100373,0.00003190456,0.00002906465,0.00003145145],"domain_scores_gemma":[0.9997136,0.00009754539,0.00005740772,0.00002827363,0.00006734455,0.0000357785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001364504,0.00059629,0.3789855,0.0002726797,0.0008568196,0.0006875881,0.0002900823,0.1321994,0.3492787,0.0007262014,0.001644522,0.1330978],"study_design_scores_gemma":[0.0001364768,0.0001141655,0.3412844,0.0000296358,0.0002061066,0.0001228934,0.0001124961,0.6159956,0.04067516,0.0002974804,0.0009718101,0.00005378017],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955218,0.0004019431,0.0027357,0.00002763757,0.00002784461,0.00001329013,0.0004234472,0.0002055019,0.0006428839],"genre_scores_gemma":[0.9966497,0.0001352489,0.002419329,0.00001416305,0.00001700328,0.000004419905,0.0005913313,0.00002180634,0.0001471074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01782835,"threshold_uncertainty_score":0.03544915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03504264256974492,"score_gpt":0.2734642980186485,"score_spread":0.2384216554489035,"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."}}