{"id":"W2499950088","doi":"","title":"Efficient Calibration of Computationally Intensive Hydrological Models","year":2015,"lang":"en","type":"article","venue":"2015 AGU Fall Meeting","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Calibration; Computer science; Environmental science; Remote sensing; Geology; Mathematics; Statistics","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":[0.001297821,0.0007862396,0.0007162007,0.0006194329,0.0007066079,0.001464554,0.001814183,0.001184119,0.004307111],"category_scores_gemma":[0.008434657,0.0009295794,0.0005885662,0.0008500423,0.0004688534,0.001540017,0.001868467,0.001877486,0.001003632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136146,"about_ca_system_score_gemma":0.00274361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01184714,"about_ca_topic_score_gemma":0.01228743,"domain_scores_codex":[0.9994357,0.0001955524,0.00003252698,0.00009592267,0.0001706017,0.00006968114],"domain_scores_gemma":[0.9975405,0.001439646,0.0001241252,0.0004678091,0.0003531276,0.00007476021],"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":[0.00008669343,0.00007328975,0.0009813133,0.00002564883,0.00002389671,0.00004655351,0.00004198766,0.949479,0.002477553,0.00352677,0.001300284,0.04193691],"study_design_scores_gemma":[0.00001356974,0.000005892669,0.0001480612,0.000001906631,0.000002936708,0.000005063943,0.000005671039,0.9971051,0.0008956233,0.001532421,0.000280366,0.00000338943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1582562,0.0001719465,0.8279098,0.0005525359,0.000103004,0.0001364339,0.000542324,0.006186863,0.006140925],"genre_scores_gemma":[0.7383155,0.0001064271,0.257568,0.0001258565,0.00004356164,0.000201462,0.0009072634,0.0005701348,0.002161862],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01184714,"threshold_uncertainty_score":0.02355635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0325667492703606,"score_gpt":0.2472372218660911,"score_spread":0.2146704725957305,"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."}}