{"id":"W4281635047","doi":"10.1021/acs.est.1c07819","title":"Steady-State Based Model of Airborne Particle/Gas and Settled Dust/Gas Partitioning for Semivolatile Organic Compounds in the Indoor Environment","year":2022,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Fisheries and Oceans Canada","funders":"Natural Science Foundation of Heilongjiang Province; National Natural Science Foundation of China","keywords":"Environmental science; Environmental chemistry; Particulates; Particle (ecology); Indoor air; Steady state (chemistry); Volatile organic compound; Partition coefficient; Partition (number theory); Chemistry; Work (physics); Aerosol; Environmental engineering; Chromatography; Thermodynamics; Ecology; 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":[0.0003950114,0.0004917001,0.0006232228,0.000508527,0.000570323,0.000797665,0.001032079,0.001085706,0.00248805],"category_scores_gemma":[0.0005961739,0.0003388033,0.001254544,0.0003655654,0.0005849445,0.0009003793,0.0005689234,0.0006470134,0.000612308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152023,"about_ca_system_score_gemma":0.001356517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02159921,"about_ca_topic_score_gemma":0.01089652,"domain_scores_codex":[0.9998384,0.00002717027,0.000009317841,0.00005550854,0.00004403353,0.00002571914],"domain_scores_gemma":[0.9997481,0.00009363841,0.00002894366,0.00001130105,0.0001092907,0.000008745619],"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":[0.00003275994,0.00003544025,0.001571896,0.0000791229,0.00003024222,0.00009191618,0.0000893398,0.9758587,0.009275449,0.007578643,0.0005027315,0.004853818],"study_design_scores_gemma":[0.000003529521,0.00001205698,0.0002742387,0.000003367835,0.000009741204,0.000008691622,0.000007392802,0.9979019,0.0006300272,0.0007510909,0.0003924347,0.000005611594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1870048,0.001028201,0.7856947,0.0005154107,0.0001590805,0.0001866171,0.001116106,0.0006923664,0.0236027],"genre_scores_gemma":[0.9407682,0.0008772485,0.03385745,0.0001833179,0.0000444067,0.0004896097,0.0007645425,0.0001018345,0.02291332],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02159921,"threshold_uncertainty_score":0.04294693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02166597645194127,"score_gpt":0.24978409893533,"score_spread":0.2281181224833887,"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."}}