{"id":"W2306571391","doi":"10.14796/jwmm.r228-12","title":"Extrapolation of Available Monitoring Data to Facilitate Long-Term Continuous Simulation Modeling","year":2008,"lang":"en","type":"article","venue":"Journal of Water Management Modeling","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extrapolation; Combined sewer; Sanitary sewer; Term (time); Plan (archaeology); Control (management); Computer science; Environmental science; Environmental engineering; Geography; Archaeology; Mathematics; Artificial intelligence; Statistics; Stormwater","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":[0.001386319,0.0005798471,0.0003988658,0.0006392325,0.0003341967,0.0007959536,0.0008779311,0.0006374947,0.003108147],"category_scores_gemma":[0.00432026,0.0003517834,0.0007135311,0.0008535873,0.000143266,0.001156448,0.0003906821,0.00100989,0.0007609864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008418799,"about_ca_system_score_gemma":0.000797121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03383201,"about_ca_topic_score_gemma":0.02190095,"domain_scores_codex":[0.9996723,0.0001175846,0.00003164105,0.00007565578,0.00007404049,0.00002874825],"domain_scores_gemma":[0.9982082,0.0007753498,0.0001376115,0.0003583651,0.0004658252,0.00005472233],"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":[0.00006846356,0.0001663826,0.01159315,0.00006125731,0.00004775786,0.00005754608,0.00004979918,0.9622803,0.001541531,0.001410797,0.001891908,0.0208311],"study_design_scores_gemma":[0.00001731631,0.00003660849,0.004408096,0.0000170019,0.00001668164,0.00001281116,0.00001717816,0.9911727,0.001391362,0.0008344532,0.002062102,0.000013698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5550049,0.0003396968,0.3868299,0.0005537811,0.000265035,0.000497523,0.0175351,0.006126978,0.03284715],"genre_scores_gemma":[0.9456956,0.0001594064,0.04456622,0.00004837004,0.00001672407,0.000281235,0.006483697,0.000164352,0.002584367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03383201,"threshold_uncertainty_score":0.06727016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1635555803935944,"score_gpt":0.2808104555527117,"score_spread":0.1172548751591173,"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."}}