{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003143692,0.0001317238,0.000190419,0.0001537341,0.00002636881,0.00003074387,0.00009076174,0.0001422801,0.000009322921],"category_scores_gemma":[0.0008727468,0.0001376836,0.00004841802,0.0001251484,0.000009412103,0.0002881338,0.000009497142,0.0001425946,0.000001366578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002001808,"about_ca_system_score_gemma":0.00007330062,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009421694,"about_ca_topic_score_gemma":0.01177851,"domain_scores_codex":[0.9987952,0.0001434163,0.0004767281,0.0001571499,0.0002330224,0.0001944712],"domain_scores_gemma":[0.9991264,0.0003499869,0.00008572809,0.0001651484,0.0002253158,0.00004746393],"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":[0.000002891779,0.00001499501,0.001532629,0.00003300271,0.00001209665,5.028565e-8,0.0002854599,0.9927029,0.00268573,0.00001325593,0.00001720329,0.002699765],"study_design_scores_gemma":[0.0004961769,0.00001811059,0.006233901,0.00003907466,0.00003026807,3.501986e-7,0.00001456538,0.9889043,0.002662199,0.001454714,0.00001750648,0.0001288113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5438349,0.00004650132,0.4536014,0.00001405875,0.00008542826,0.0003292882,7.882804e-7,0.0000702922,0.002017386],"genre_scores_gemma":[0.5615457,0.000003270763,0.4382989,0.000005040722,0.00001163357,0.00008063167,0.00001762482,0.00001610442,0.00002112391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01771083,"threshold_uncertainty_score":0.9971747,"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."}}