{"id":"W2557814580","doi":"","title":"A Robust Computational Method for Coupled Liquid-liquid Phase Separation and Gas-particle Partitioning Predictions of Multicomponent Aerosols","year":2014,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Particle Dynamics in Fluid Flows","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Particle (ecology); Separation (statistics); Liquid liquid; Gas phase; Environmental science; Liquid phase; Phase (matter); Process engineering; Materials science; Chromatography; Chemistry; Thermodynamics; Computer science; Physics; Engineering; Geology","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":[0.0008384461,0.0001660113,0.0002375509,0.00005448774,0.000155291,0.00004386833,0.00008326041,0.00008289247,0.000001500975],"category_scores_gemma":[0.0004240805,0.0001920811,0.00005883381,0.0001023301,0.00005391502,0.0001829109,0.00002473792,0.0001216099,0.000005890633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005646401,"about_ca_system_score_gemma":0.00001762054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001501338,"about_ca_topic_score_gemma":0.0001957989,"domain_scores_codex":[0.9986164,0.00005887392,0.0005859143,0.0002360716,0.0001969313,0.000305832],"domain_scores_gemma":[0.9986153,0.0008140964,0.0001245687,0.0001653535,0.0001459133,0.0001347794],"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":[0.000106637,0.0001018835,0.0002251896,0.00007395315,0.00004193564,5.721508e-7,0.0003800244,0.8354755,0.1630048,0.000365412,0.00003266686,0.0001914106],"study_design_scores_gemma":[0.001653391,0.0002954496,0.001184755,0.00009811643,0.00006002271,0.000007826483,0.0000410769,0.9755979,0.02069238,0.0001308846,0.00006606102,0.0001721288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6968178,0.00003556655,0.3023056,0.00007201963,0.0001335517,0.0002619113,0.00002630949,0.0001760818,0.0001711695],"genre_scores_gemma":[0.903497,0.000009895477,0.09617761,0.0000244593,0.0000843192,0.0001024907,0.00006695676,0.00003323262,0.000003986421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2066793,"threshold_uncertainty_score":0.7832841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02733994244916032,"score_gpt":0.2975264386423869,"score_spread":0.2701864961932266,"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."}}