{"id":"W4243033509","doi":"10.32920/ryerson.14668281","title":"Automating GIS input for distributed urban drainage modelling","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Natural Sciences and Engineering Research Council of Canada","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Drainage; Environmental science; Rain gauge; Stormwater; Hydrology (agriculture); Geographic information system; Precipitation; Computer science; Water resource management; Environmental resource management; Surface runoff; Remote sensing; Meteorology; Geography; Geology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001059846,0.00112233,0.0006067907,0.001380309,0.000567916,0.001898267,0.001380825,0.0004444878,0.009461264],"category_scores_gemma":[0.004761496,0.0007494061,0.0007638537,0.001582793,0.0003759857,0.001135651,0.001443944,0.0008086606,0.00243398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001351315,"about_ca_system_score_gemma":0.001471634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01366088,"about_ca_topic_score_gemma":0.02036068,"domain_scores_codex":[0.9995049,0.0001013856,0.00004068663,0.0001094678,0.0002062548,0.00003738804],"domain_scores_gemma":[0.9985032,0.0006320472,0.00006469701,0.0003116327,0.000442769,0.00004563687],"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":[0.0001922259,0.0002027912,0.01102783,0.000408799,0.0001011218,0.000521333,0.001373604,0.7148474,0.01358909,0.01318155,0.03347993,0.2110742],"study_design_scores_gemma":[0.00005160077,0.00002365815,0.001857149,0.00005121405,0.00002362615,0.00006461443,0.0002880454,0.9413996,0.01397828,0.006788271,0.03543834,0.00003563131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07336371,0.00007218385,0.8271952,0.0002897635,0.0001114624,0.0005780849,0.01037623,0.07333305,0.0146803],"genre_scores_gemma":[0.4443072,0.0001632234,0.5322844,0.00009750031,0.00001904591,0.0007020383,0.01329078,0.003535109,0.005600654],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01366088,"threshold_uncertainty_score":0.03165102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02921689445474435,"score_gpt":0.2370588068865799,"score_spread":0.2078419124318356,"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."}}