{"id":"W4220812548","doi":"10.5194/acp-2022-179","title":"Contributions of primary sources to submicron organic aerosols in Delhi, India","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"University of Texas at Austin; University of Rochester; Indian Institute of Technology Delhi; ClimateWorks Foundation; Helsingin Yliopisto; Welch Foundation; National Science Foundation","keywords":"Aerosol; Biomass burning; Environmental science; Monsoon; New delhi; Atmospheric sciences; Environmental chemistry; Chemistry; Meteorology; 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":[0.000208652,0.000521306,0.0001983581,0.0008965894,0.0006003939,0.0008032898,0.0004198395,0.0003640075,0.0009462901],"category_scores_gemma":[0.0002667514,0.0002088357,0.0006385661,0.0008796133,0.000274512,0.0003792813,0.0005003294,0.000386057,0.0003046203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008285062,"about_ca_system_score_gemma":0.000616928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07654339,"about_ca_topic_score_gemma":0.087038,"domain_scores_codex":[0.9998314,0.0000130025,0.000006889867,0.00004293266,0.00004707081,0.00005865626],"domain_scores_gemma":[0.999813,0.0000407894,0.00002965967,0.00001621333,0.00007282726,0.00002752479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007260164,0.0002539518,0.7023723,0.0004835332,0.0004386171,0.002535803,0.001479091,0.03185916,0.1696543,0.001450505,0.006042441,0.08270444],"study_design_scores_gemma":[0.00003022972,0.00009277248,0.9236994,0.00002533418,0.0002096034,0.0003605887,0.001435274,0.038513,0.02969231,0.0004770341,0.005403592,0.00006094016],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994194,0.0001922362,0.00149496,0.0001549922,0.00004068487,0.00001683451,0.001249638,0.0002101062,0.00244652],"genre_scores_gemma":[0.9972963,0.000109201,0.001032837,0.00003363155,0.00001827644,0.000006577347,0.0009391474,0.00003192978,0.0005321678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07654339,"threshold_uncertainty_score":0.1521957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00984573063820228,"score_gpt":0.2144073000464073,"score_spread":0.204561569408205,"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."}}