{"id":"W2346293290","doi":"10.1080/02786826.2016.1185509","title":"Methodology for quantifying the volatile mixing state of an aerosol","year":2016,"lang":"en","type":"article","venue":"Aerosol Science and Technology","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Alberta","funders":"","keywords":"Aerosol; Differential mobility analyzer; Soot; Chemistry; Particle (ecology); Mixing (physics); Scanning mobility particle sizer; Condensation particle counter; Particle number; Carbon fibers; Analytical Chemistry (journal); Particle counter; Chemical composition; Population; Particle size; Particle-size distribution; Environmental chemistry; Combustion; Materials science; Thermodynamics; Organic chemistry","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":[0.001812301,0.0009080817,0.0004988025,0.00321248,0.0007648763,0.0007303018,0.001161354,0.0009347805,0.001307648],"category_scores_gemma":[0.002088889,0.0004576884,0.0004532164,0.001484331,0.0004041436,0.0006449706,0.0008917851,0.001001308,0.0007081203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007367837,"about_ca_system_score_gemma":0.001228367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001647886,"about_ca_topic_score_gemma":0.003102288,"domain_scores_codex":[0.9978451,0.000251718,0.0001279092,0.0004951979,0.001200294,0.0000798505],"domain_scores_gemma":[0.9987343,0.0002422106,0.0002446867,0.0001555984,0.0005769025,0.00004631505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001167746,0.0002027365,0.0151871,0.0005800308,0.0001497172,0.0001547796,0.0001875428,0.00260237,0.8613362,0.002451598,0.0008135837,0.1162177],"study_design_scores_gemma":[0.00005379051,0.0006988611,0.02837204,0.00009662772,0.0001332812,0.0009415628,0.0001409586,0.06166283,0.8903761,0.001898303,0.01546895,0.0001566813],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06867748,0.001440635,0.9241328,0.00008298974,0.000125503,0.001081325,0.001033666,0.001182445,0.002243183],"genre_scores_gemma":[0.1967247,0.001145329,0.797307,0.0001205742,0.00004013885,0.001900716,0.0008365871,0.0001010048,0.001823939],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00321248,"threshold_uncertainty_score":0.009584427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05669247514931567,"score_gpt":0.2920861422498983,"score_spread":0.2353936671005827,"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."}}