{"id":"W3127120842","doi":"10.1016/j.chemosphere.2021.129913","title":"Chemical source profiles of fine particles for five different sources in Delhi","year":2021,"lang":"en","type":"article","venue":"Chemosphere","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"University of Surrey; Ministry of Earth Sciences; Natural Environment Research Council; Sight Research UK","keywords":"Environmental chemistry; Total organic carbon; Particulates; Crop residue; Environmental science; Pollution; Biomass burning; Pollutant; Air pollution; Organic matter; Aerosol; Municipal solid waste; Chemical composition; Carbon fibers; Chemistry; Environmental engineering; Waste management; Materials science; Agriculture","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001164811,0.00009334191,0.0001958695,0.000002380677,0.00003681556,0.000008021567,0.0001043795,0.00007326365,0.001274263],"category_scores_gemma":[0.0001918945,0.00008079554,0.000050347,0.000107971,0.0001162321,0.00005451292,0.0001032401,0.00007992575,0.00002428526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006874167,"about_ca_system_score_gemma":0.00002223828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001092924,"about_ca_topic_score_gemma":0.0002954747,"domain_scores_codex":[0.9991127,0.00002675583,0.0002440167,0.0002069541,0.0001404722,0.0002690489],"domain_scores_gemma":[0.9995265,0.0001280052,0.0000719283,0.0001588433,0.000009701368,0.0001050173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000351942,0.001442976,0.5190263,0.0009854469,0.00003207164,0.00001094222,0.01048313,0.001691393,0.2559106,0.0002997586,0.02845833,0.181307],"study_design_scores_gemma":[0.0007244144,0.00004246206,0.03912533,0.00005508438,0.000008494569,0.000002385957,0.0009313799,0.002602638,0.9520542,0.001179004,0.003139673,0.0001349009],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963964,0.0001619805,0.0004773668,0.002275262,0.00001894559,0.0001706858,0.000008292229,0.0000154954,0.0004755538],"genre_scores_gemma":[0.9923444,0.000005681872,0.006239019,0.0004853584,0.00003034178,0.00003192846,0.00001254708,0.00001007175,0.0008406695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6961436,"threshold_uncertainty_score":0.9996387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02761815609344202,"score_gpt":0.2779822612387776,"score_spread":0.2503641051453356,"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."}}