{"id":"W2104761232","doi":"10.1002/qj.2647","title":"Satellite‐based estimation of cloud‐base heights using constrained spectral radiance matching","year":2015,"lang":"en","type":"article","venue":"Quarterly Journal of the Royal Meteorological Society","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Environment and Climate Change Canada","funders":"National Natural Science Foundation of China; National Aeronautics and Space Administration","keywords":"Radiance; Remote sensing; Cloud computing; Satellite; Environmental science; Computer science; Cloud fraction; Cloud top; Matching (statistics); Satellite imagery; Meteorology; Algorithm; Cloud cover; Geology; Mathematics; Physics; Statistics","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":[0.0009183874,0.0001677185,0.0003306736,0.000001379217,0.0001336886,0.00002871247,0.0004084188,0.0001286567,0.0002978452],"category_scores_gemma":[0.00004535453,0.00009702132,0.000441246,0.0001737664,0.000483768,0.0001238349,0.00003666224,0.0003250214,0.000009095253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000208424,"about_ca_system_score_gemma":0.00005638718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009078164,"about_ca_topic_score_gemma":0.000003956013,"domain_scores_codex":[0.9982523,0.0002286506,0.0005404925,0.000161186,0.0005374553,0.0002799534],"domain_scores_gemma":[0.998838,0.000115928,0.0006226139,0.0001831494,0.00003248997,0.0002078101],"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":[0.0004163564,0.0005347424,0.02606618,0.00002979269,0.0001601855,0.00004088003,0.005591997,0.920726,0.01570928,0.000553436,0.001055216,0.02911593],"study_design_scores_gemma":[0.005019157,0.005438169,0.0630862,0.000167915,0.0004084288,0.0001959732,0.003550002,0.8572828,0.007545017,0.05599613,0.0004908483,0.0008193394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9493767,0.0001354216,0.04929547,0.0004409441,0.0003060925,0.0001102564,0.000002998247,0.00001050755,0.0003216054],"genre_scores_gemma":[0.9155875,0.000002039243,0.08398867,0.000273361,0.0001104521,7.634496e-7,3.908287e-7,0.000008230307,0.00002854399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06344319,"threshold_uncertainty_score":0.3956414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02380384386718307,"score_gpt":0.2449052742785766,"score_spread":0.2211014304113935,"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."}}