{"id":"W6940646726","doi":"10.1021/acs.est.9b02461.s001","title":"Source Contributions to Ambient Fine Particulate Matter\\nfor Canada","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Air quality index; Particulates; Air pollution; Acid rain; Trend analysis; Nitrogen oxides","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004040339,0.0007175992,0.0003741277,0.001484848,0.00171024,0.001248755,0.0008125718,0.0003229374,0.006905708],"category_scores_gemma":[0.001022496,0.0003375387,0.001359753,0.003195642,0.0003106114,0.0005387266,0.001138419,0.0005441759,0.0009889336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01955262,"about_ca_system_score_gemma":0.03519034,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946326,"about_ca_topic_score_gemma":0.9942915,"domain_scores_codex":[0.9993136,0.0000269955,0.00002719815,0.0001153544,0.0003356495,0.000181211],"domain_scores_gemma":[0.999289,0.00002886412,0.00004253937,0.00002690416,0.0005656602,0.00004700639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003741555,0.00008780373,0.7833722,0.0008800422,0.0008719497,0.0006405406,0.001107192,0.0169689,0.004379143,0.008576536,0.0940017,0.08873989],"study_design_scores_gemma":[0.0000639559,0.00002533833,0.8561096,0.0003314862,0.0003569862,0.0002149096,0.00149805,0.01721252,0.003106928,0.001608288,0.119337,0.0001349233],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6346958,0.007756027,0.009872704,0.004194995,0.0004880679,0.0003702394,0.2283201,0.001373869,0.1129281],"genre_scores_gemma":[0.9081892,0.005376695,0.003855536,0.0006406823,0.00005504863,0.00009107077,0.04870165,0.0002691514,0.03282094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01955262,"threshold_uncertainty_score":0.1418648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01028754803267086,"score_gpt":0.2036229910311797,"score_spread":0.1933354429985089,"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."}}