{"id":"W3107152720","doi":"","title":"The Canadian Hydrological Model (CHM): A multi-scale, variable-complexity hydrological model for cold regions","year":2016,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Scale (ratio); Variable (mathematics); Environmental science; Hydrological modelling; Water cycle; Climatology; Hydrology (agriculture); Meteorology; Geography; Mathematics; Geology; Cartography; Ecology","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":[0.000643256,0.001015339,0.0008235313,0.001117015,0.002048187,0.001659065,0.004120461,0.001008091,0.007292263],"category_scores_gemma":[0.002524696,0.0007780723,0.001033651,0.002716805,0.0006476738,0.00161402,0.0009209557,0.001736963,0.001099797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01474581,"about_ca_system_score_gemma":0.02910011,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9758814,"about_ca_topic_score_gemma":0.9767715,"domain_scores_codex":[0.9996563,0.0000469031,0.00001383782,0.00005793284,0.0001459655,0.000079095],"domain_scores_gemma":[0.9990981,0.00009794597,0.0000480054,0.00006306143,0.0005321811,0.0001608226],"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":[0.0001589654,0.000130132,0.01028552,0.0001120561,0.0001925068,0.00008571212,0.0001220958,0.8607518,0.001287923,0.01005718,0.08242059,0.03439543],"study_design_scores_gemma":[0.0001769286,0.000008703682,0.008296417,0.00001781912,0.00005243258,0.00001376918,0.00004447541,0.9650528,0.0004982224,0.002332661,0.0234007,0.0001050495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3955566,0.002032354,0.1929705,0.008168588,0.0008520595,0.001140179,0.2918071,0.02996742,0.07750509],"genre_scores_gemma":[0.7453504,0.001665941,0.1520074,0.0006691974,0.000146957,0.0007465041,0.0791297,0.0031473,0.01713667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0241186,"threshold_uncertainty_score":0.1069888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05774166455356233,"score_gpt":0.2531004774394779,"score_spread":0.1953588128859156,"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."}}