{"id":"W2078932557","doi":"10.1029/2009jd013019","title":"Detecting thin cirrus in Multiangle Imaging Spectroradiometer aerosol retrievals","year":2010,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Cirrus; Aerosol; Spectroradiometer; Remote sensing; Environmental science; Lidar; AERONET; Latitude; Satellite; Optical depth; Atmospheric sciences; Meteorology; Physics; Optics; Geology; Reflectivity; Astronomy","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":[0.001495984,0.0007833962,0.0004829629,0.001803099,0.000314677,0.001039571,0.0006513015,0.0005033318,0.0007593976],"category_scores_gemma":[0.00340372,0.0003810245,0.0005640897,0.0007519302,0.0002919713,0.001238728,0.0009089975,0.0004369329,0.0007084025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004141663,"about_ca_system_score_gemma":0.0005386206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009183249,"about_ca_topic_score_gemma":0.01313615,"domain_scores_codex":[0.9991537,0.0001348944,0.00005446065,0.0001533846,0.000351953,0.0001515386],"domain_scores_gemma":[0.9990759,0.0002350896,0.0001460567,0.0001578597,0.0002987785,0.00008631039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005609004,0.0001815167,0.2085424,0.0003543737,0.0003579022,0.0007747057,0.0004921456,0.0745386,0.409392,0.00178955,0.005130987,0.2978849],"study_design_scores_gemma":[0.0001195414,0.0003232095,0.2812424,0.0001240657,0.0002536566,0.0008802311,0.0003788144,0.5677534,0.1340389,0.002086575,0.01263435,0.0001648944],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8848326,0.002031924,0.1023817,0.0003517728,0.0002142141,0.00009791195,0.001046965,0.002039899,0.007002913],"genre_scores_gemma":[0.9219854,0.0004112822,0.07520635,0.0001669382,0.00007628699,0.00001914882,0.001322219,0.000178402,0.0006339559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009183249,"threshold_uncertainty_score":0.01825958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01981090080165442,"score_gpt":0.3100305262909088,"score_spread":0.2902196254892543,"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."}}