{"id":"W7002203338","doi":"","title":"Modeling aerosol puff concentration distributions from point sources using artificial neural networks","year":2000,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Homicide, Infanticide, and Child Abuse","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Aerosol; Point (geometry); Feature (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003224424,0.0006863582,0.0003972644,0.0006319327,0.000361849,0.0006212415,0.0009166516,0.00116526,0.0009426362],"category_scores_gemma":[0.001446086,0.0005144974,0.0005725157,0.0006287208,0.0003219886,0.0006506541,0.0003340419,0.0006878086,0.0002017497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414891,"about_ca_system_score_gemma":0.0009651736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1018863,"about_ca_topic_score_gemma":0.06681845,"domain_scores_codex":[0.9999093,0.00001400976,0.000005068498,0.00002575449,0.00003301283,0.0000127715],"domain_scores_gemma":[0.9994926,0.0003148426,0.00004593144,0.00001721255,0.0001149218,0.00001437075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001358119,0.00001272996,0.0008638385,0.000007282936,0.00001222431,0.00002283276,0.000005197439,0.9944088,0.0002904294,0.0001888041,0.0001393304,0.004034956],"study_design_scores_gemma":[0.000001589854,0.00000113961,0.0001528665,4.963766e-7,0.000001310205,0.00000170695,8.312792e-7,0.9995837,0.000107216,0.0001230128,0.00002499474,0.000001175464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.601411,0.001065941,0.3832209,0.0006030865,0.0001772131,0.0001221811,0.001371701,0.001617157,0.0104109],"genre_scores_gemma":[0.9649917,0.0003327127,0.02755429,0.00004991984,0.00005611738,0.00007505735,0.0006435722,0.00006286869,0.006233842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1018863,"threshold_uncertainty_score":0.2025866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006932174021882911,"score_gpt":0.176511483328552,"score_spread":0.169579309306669,"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."}}