{"id":"W2990696444","doi":"","title":"Evaluation of Optimization Methods for Hydrologic Model Calibration in Ontario Basins","year":2013,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Calibration; Hydrological modelling; Environmental science; Hydrology (agriculture); Geology; Mathematics; Climatology; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004888954,0.0009524254,0.0006964032,0.00102772,0.0008216958,0.001123606,0.001102059,0.001112618,0.001333498],"category_scores_gemma":[0.01436213,0.0005827786,0.0006051758,0.000950739,0.0006232778,0.0009976983,0.0009179894,0.00068792,0.0001418534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002873593,"about_ca_system_score_gemma":0.003267665,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1478913,"about_ca_topic_score_gemma":0.1149018,"domain_scores_codex":[0.9988036,0.0006819827,0.00007765429,0.0001413587,0.0002038017,0.000091539],"domain_scores_gemma":[0.9931738,0.005005904,0.0003570295,0.0003348572,0.001032718,0.00009563817],"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":[0.0001469345,0.00006830237,0.003360962,0.00003622627,0.00004304167,0.00001446762,0.00004002978,0.9712227,0.0005634981,0.0007052505,0.0002359104,0.02356279],"study_design_scores_gemma":[0.00001601518,0.00001795862,0.0008593836,0.000004495397,0.000006679215,0.000002392597,0.00001204912,0.998235,0.0006005759,0.0001423271,0.00009885225,0.000004324806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7997106,0.0005860912,0.1896707,0.0005560077,0.00003807,0.0002150255,0.000518055,0.001355178,0.007350233],"genre_scores_gemma":[0.9412178,0.0001215063,0.05683363,0.000053878,0.000008958538,0.00008362043,0.0003792821,0.0002100294,0.00109142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8521087,"threshold_uncertainty_score":0.2940609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06476910176992791,"score_gpt":0.3268784419730444,"score_spread":0.2621093402031165,"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."}}