{"id":"W2911806957","doi":"10.5194/acp-19-8879-2019","title":"Is positive correlation between cloud droplet effective radius and aerosol optical depth over land due to retrieval artifacts or real physical processes?","year":2019,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ocean Networks Canada Society; University of Victoria","funders":"Government of Jiangsu Province; National Natural Science Foundation of China; National Aeronautics and Space Administration","keywords":"Aerosol; Effective radius; Liquid water path; Environmental science; Moderate-resolution imaging spectroradiometer; Atmospheric sciences; Cloud top; Liquid water content; Meteorology; Climatology; Cloud computing; Satellite; Geology; Geography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001153492,0.0002409799,0.0003256534,0.000464267,0.0002195023,0.0006381244,0.000483589,0.0003196534,0.001186708],"category_scores_gemma":[0.004384551,0.0001841157,0.0004470439,0.0007401634,0.0006824961,0.0008156259,0.0003378047,0.0001935296,0.0002941851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003189,"about_ca_system_score_gemma":0.0003239846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004115677,"about_ca_topic_score_gemma":0.003303253,"domain_scores_codex":[0.9992705,0.0001542919,0.00008058667,0.0002358935,0.0001551926,0.0001035102],"domain_scores_gemma":[0.9945371,0.002245188,0.001939583,0.0005573988,0.0005988614,0.0001218634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006845785,0.00001376439,0.985233,0.00006322126,0.0001528662,0.000290164,0.00005005551,0.0009860314,0.006812138,0.0001466728,0.0001422393,0.00604147],"study_design_scores_gemma":[0.000006173417,0.00003110352,0.9897168,0.00001144686,0.00006884939,0.000256743,0.0001214683,0.006567231,0.002668197,0.00021355,0.0003287143,0.000009650483],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950777,0.0008904099,0.002791529,0.0001607108,0.00001939535,0.00001000341,0.0003259543,0.00004135472,0.0006827399],"genre_scores_gemma":[0.9994649,0.0000643236,0.0002535045,0.00002284613,0.00001602484,0.00000187353,0.0001213083,0.00000717222,0.00004800485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004115677,"threshold_uncertainty_score":0.00818342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005118729572245155,"score_gpt":0.2275903694109147,"score_spread":0.2224716398386695,"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."}}