{"id":"W4241703595","doi":"10.5194/acp-2018-459","title":"Interpretation of Measured Aerosol Mass Scattering Efficiency Over North America Using a Chemical Transport Model","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Health Effects Institute; U.S. Environmental Protection Agency","keywords":"Aerosol; Scattering; Atmospheric sciences; Environmental science; Particle (ecology); Visibility; Mass concentration (chemistry); Computational physics; Physics; Meteorology; Optics; Geology; Thermodynamics","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":[0.0005411003,0.0005281586,0.0001998213,0.000387859,0.0003765515,0.0005615925,0.00043854,0.000379125,0.0005873828],"category_scores_gemma":[0.0009350218,0.0002785191,0.0004109584,0.0004927123,0.0002958697,0.0005485977,0.0002757756,0.0002668992,0.00009508982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002521701,"about_ca_system_score_gemma":0.001051596,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2275115,"about_ca_topic_score_gemma":0.1760868,"domain_scores_codex":[0.9998336,0.00004995957,0.00001076322,0.00005582617,0.00002976743,0.00002003194],"domain_scores_gemma":[0.9996554,0.0001096348,0.00005831966,0.00004353838,0.0001123406,0.00002081414],"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":[0.0001596373,0.00007951898,0.3436044,0.00006147799,0.0002213177,0.0001860351,0.0001754849,0.6227521,0.02343601,0.001239192,0.001014953,0.007069901],"study_design_scores_gemma":[0.00005230562,0.00003738235,0.188033,0.00001178127,0.00005470353,0.00005109893,0.0001421128,0.802124,0.007764001,0.0005421909,0.001162257,0.00002516894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953896,0.00005393815,0.002238848,0.0001302826,0.000006460924,0.00001331157,0.000705211,0.0001206069,0.001341761],"genre_scores_gemma":[0.9981834,0.00003170004,0.001182117,0.00001832068,0.000002575469,0.000007773499,0.0003838397,0.00001608139,0.0001740326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7724885,"threshold_uncertainty_score":0.4523745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0160467056514822,"score_gpt":0.237563411323367,"score_spread":0.2215167056718848,"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."}}