{"id":"W2515552876","doi":"","title":"A New Wavelet Based Approach to Assess Hydrological Models","year":2014,"lang":"en","type":"article","venue":"2014 AGU Fall Meeting","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Wavelet; Computer science; Artificial intelligence; Environmental science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001466366,0.0002680438,0.0003104458,0.00004479466,0.0002114775,0.00008163175,0.0005978004,0.0001939015,0.0001817012],"category_scores_gemma":[0.0005681831,0.0002141653,0.00009906309,0.0002514866,0.00009160835,0.000129446,0.0003937173,0.0002897016,0.001396626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001109276,"about_ca_system_score_gemma":0.00001330051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001690689,"about_ca_topic_score_gemma":0.0001021002,"domain_scores_codex":[0.9973977,0.0002712705,0.0003263798,0.000778183,0.0005183971,0.0007080746],"domain_scores_gemma":[0.9987172,0.0002518229,0.0001074683,0.0004486305,0.000009848492,0.0004649809],"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":[0.0000291815,0.0001200448,0.01339007,0.000008983705,0.000005589222,0.000003855918,0.0001387301,0.9574273,0.002440521,0.0005597882,0.01255497,0.013321],"study_design_scores_gemma":[0.0003136169,0.0001722004,0.00262515,0.00002117952,0.00001260452,0.000007582593,0.000003802335,0.9873065,0.000239458,0.002567949,0.006382968,0.0003469519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5527834,0.000007210914,0.2875624,0.0005332103,0.00008715533,0.0002175262,0.000001229483,0.0002408102,0.1585671],"genre_scores_gemma":[0.787563,3.223052e-7,0.2094937,0.002392559,0.0001291812,0.00001779266,0.000005831848,0.0000251658,0.0003723645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2347797,"threshold_uncertainty_score":0.9993809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05183380909433727,"score_gpt":0.2465586928622782,"score_spread":0.1947248837679409,"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."}}