{"id":"W1520072003","doi":"10.1002/9780470515600.ch6","title":"Measuring and Modelling Pollution for Risk Analysis","year":2007,"lang":"en","type":"review","venue":"Novartis Foundation symposium","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; University of British Columbia","funders":"","keywords":"Sketch; Computer science; Scale (ratio); Perspective (graphical); Air quality index; Population; Regression analysis; Data science; Operations research; Risk analysis (engineering); Econometrics; Meteorology; Geography; Engineering; Machine learning; Artificial intelligence; Cartography; Mathematics; Algorithm","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":[0.004938367,0.002057627,0.002634691,0.004393694,0.000606782,0.004112909,0.002205219,0.002660105,0.004160555],"category_scores_gemma":[0.005814295,0.0006075694,0.001125463,0.005680407,0.003096049,0.004205743,0.001796184,0.004055029,0.002150157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003105957,"about_ca_system_score_gemma":0.004351964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008300621,"about_ca_topic_score_gemma":0.00647582,"domain_scores_codex":[0.9972709,0.001229817,0.0001928766,0.0002809688,0.0009566324,0.000068794],"domain_scores_gemma":[0.9969684,0.002180566,0.0001822311,0.0002388127,0.0003825584,0.00004743475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001778436,0.00008673795,0.0005982944,0.01103541,0.000254778,0.0002267998,0.0003245393,0.01300209,0.0008534297,0.2825483,0.04142567,0.6496262],"study_design_scores_gemma":[0.000007892266,0.00005496703,0.0007946334,0.005733848,0.0001018933,0.0003661348,0.0003206104,0.003746098,0.0006231638,0.2398081,0.7483807,0.00006195092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003123142,0.9466574,0.03787072,0.005126469,0.0007859595,0.00005817731,0.0001389263,0.00009431681,0.008955577],"genre_scores_gemma":[0.008398083,0.964814,0.02208555,0.0009629171,0.000651986,0.0001437404,0.0001515161,0.00003280917,0.00275944],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.008300621,"threshold_uncertainty_score":0.02611685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2197164660876317,"score_gpt":0.3869701992041307,"score_spread":0.167253733116499,"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."}}