{"id":"W26675013","doi":"10.15557/jou.2013.0043","title":"Automatic Calibration of Hydrological Models in the Newly Reconstructed Catchments: Issues, Methods and Uncertainties","year":2010,"lang":"en","type":"article","venue":"EGU General Assembly Conference Abstracts","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Calibration; Environmental science; Remote sensing; Hydrological modelling; Computer science; Geology; Climatology; 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":[0.006247417,0.0005474467,0.0007705692,0.001082215,0.0006316198,0.001786843,0.001500535,0.0008661036,0.001112242],"category_scores_gemma":[0.01829216,0.0006027645,0.0007138369,0.001481009,0.0005480092,0.001331115,0.0009861337,0.001114745,0.0006313966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007876753,"about_ca_system_score_gemma":0.001449137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01505585,"about_ca_topic_score_gemma":0.0134762,"domain_scores_codex":[0.9980855,0.001141265,0.0001175987,0.0003577249,0.0002191391,0.00007883571],"domain_scores_gemma":[0.9929675,0.004249133,0.0003970515,0.001134509,0.001113972,0.0001379206],"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":[0.0002032934,0.00008392255,0.03191539,0.0001463049,0.0002358515,0.00008010046,0.0003173873,0.7912931,0.00307546,0.003133154,0.001028508,0.1684875],"study_design_scores_gemma":[0.00001790873,0.000009714843,0.004578238,0.00001961827,0.00001429936,0.00002447317,0.00004930435,0.9920773,0.0009230048,0.001433058,0.0008337233,0.00001937182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1382352,0.0004604714,0.8556107,0.0004948639,0.00009268108,0.0001106011,0.0004905752,0.002863554,0.001641216],"genre_scores_gemma":[0.7823686,0.0002221213,0.2156813,0.00007268022,0.00004795593,0.0001261114,0.0005490766,0.0003633018,0.000568939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01505585,"threshold_uncertainty_score":0.03303987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02887749142470979,"score_gpt":0.300294935594084,"score_spread":0.2714174441693742,"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."}}