{"id":"W2116157165","doi":"10.1002/met.1523","title":"Field trial of an automated ground‐based infrared cloud classification system","year":2015,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Campbell Scientific (Canada)","funders":"Met Office; Loughborough University; Technology Strategy Board","keywords":"Cloud computing; Remote sensing; Radar; Computer science; Meteorology; Environmental science; Lightning (connector); Field (mathematics); Detector; Infrared; Lightning detection; Real-time computing; Geology; Telecommunications; Thunderstorm; Geography; Operating system; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005289415,0.0001361605,0.0002161758,0.00004215263,0.0001437822,0.00002943088,0.000367521,0.0001842487,0.00008649748],"category_scores_gemma":[0.00009602898,0.0001133969,0.00007214522,0.000537289,0.0001905759,0.00009183095,0.00006076665,0.0001314898,0.0003557587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001339829,"about_ca_system_score_gemma":0.00003093087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001935015,"about_ca_topic_score_gemma":0.00001534291,"domain_scores_codex":[0.9984636,0.000185383,0.000427162,0.0003958334,0.000328835,0.0001991781],"domain_scores_gemma":[0.9986086,0.000175887,0.000212033,0.0007363562,0.00004732042,0.0002197727],"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":[0.04031941,0.01679759,0.005456705,0.0002271182,0.0002626289,0.00001489635,0.001849802,0.02441937,0.2031262,0.2837426,0.07520925,0.3485745],"study_design_scores_gemma":[0.02658722,0.005271661,0.02188539,0.00002152595,0.0002383059,0.00003122343,0.00134472,0.742082,0.01137848,0.01537992,0.1747331,0.001046495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7806482,0.00001161697,0.1300681,0.0009873851,0.000145397,0.00211908,0.0000234688,0.001326793,0.08466999],"genre_scores_gemma":[0.9764264,7.589885e-7,0.02278757,0.0001898315,0.0001011895,0.0002738091,0.0000888078,0.00001154532,0.0001200733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7176626,"threshold_uncertainty_score":0.4624191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04387976260496429,"score_gpt":0.2926269365446778,"score_spread":0.2487471739397135,"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."}}