{"id":"W4391287561","doi":"","title":"Imperfect data and hydraulic modelling of urban drainage networks","year":2023,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Berger (Canada)","funders":"","keywords":"Imperfect; Computer science; Drainage network; Drainage; Ecology","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":[0.00118265,0.0003893841,0.0008884853,0.0008123855,0.0003909652,0.001530408,0.0009023181,0.001108305,0.001183352],"category_scores_gemma":[0.01117173,0.0006728317,0.0003854397,0.001262538,0.001681796,0.001894979,0.0006203118,0.0007455301,0.0001004868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001958492,"about_ca_system_score_gemma":0.001331076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03019183,"about_ca_topic_score_gemma":0.01888374,"domain_scores_codex":[0.9995525,0.0001938339,0.00002973475,0.00008984341,0.00008007698,0.00005391492],"domain_scores_gemma":[0.9950613,0.003723834,0.0004610674,0.0002826823,0.0003132967,0.0001577437],"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":[0.000004249113,0.000001960765,0.0003129463,0.00000450861,0.000001882092,0.000008045296,0.000006363211,0.9962135,0.00002367826,0.002766495,0.00005672681,0.0005995643],"study_design_scores_gemma":[9.810902e-7,0.000001451153,0.0001277547,0.000001555552,8.661552e-7,0.000002098585,0.000002856643,0.9962896,0.00003271669,0.003473724,0.00006436939,0.000002065021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4040063,0.0007409706,0.5837256,0.001827506,0.0001242208,0.00004016886,0.001386618,0.0006331955,0.007515407],"genre_scores_gemma":[0.9925737,0.0002444621,0.005105349,0.00002264181,0.00002155897,0.00002030805,0.0001812452,0.00003746275,0.001793251],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03019183,"threshold_uncertainty_score":0.06003219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02002412851799427,"score_gpt":0.2148182574538061,"score_spread":0.1947941289358118,"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."}}