{"id":"W3194964709","doi":"10.1007/s10661-021-09351-0","title":"Mobile monitoring and spatial prediction of black carbon in Cairo, Egypt","year":2021,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"International Development Research Centre","keywords":"Mean squared error; Random forest; Statistics; Environmental science; Mean absolute error; Regression; Artificial neural network; Regression analysis; Stepwise regression; Geography; Mathematics; Physical geography; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00008478283,0.0002875252,0.0002162383,0.0005216462,0.0002754477,0.0004189338,0.0003677343,0.0004852236,0.0003926088],"category_scores_gemma":[0.0001677583,0.0001062552,0.0001828355,0.0006999089,0.0001404956,0.0002287421,0.0002415585,0.000144649,0.0001024449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108591,"about_ca_system_score_gemma":0.0007998153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2510448,"about_ca_topic_score_gemma":0.2660517,"domain_scores_codex":[0.9999394,0.00000544797,0.000004216109,0.00001645042,0.00001194061,0.00002251309],"domain_scores_gemma":[0.9999272,0.00001287266,0.0000193259,0.000003486485,0.0000287812,0.000008456342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006289615,0.0003572791,0.8141733,0.0002042115,0.000353269,0.001405475,0.0007318616,0.1160608,0.01590833,0.0008248017,0.001723551,0.04762813],"study_design_scores_gemma":[0.00005220341,0.00008939928,0.7475834,0.00002651676,0.00008743369,0.0001160141,0.001832677,0.2441521,0.003922466,0.0002192589,0.001888027,0.00003053056],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988444,0.00006733048,0.0002335422,0.00005285314,0.000002911784,0.000004566241,0.0003097193,0.00001344645,0.0004713311],"genre_scores_gemma":[0.9989017,0.00005776855,0.0002841202,0.000005292722,0.000002653092,0.000004809726,0.0002594299,0.000001476105,0.0004827699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2510448,"threshold_uncertainty_score":0.4991671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02333709806800354,"score_gpt":0.3001039734490737,"score_spread":0.2767668753810702,"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."}}