{"id":"W2009487953","doi":"10.4296/cwrj3601083","title":"Reconstructing sixty year (1950-2009) daily soil moisture over the Canadian Prairies using the Variable Infiltration Capacity model","year":2011,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Hydrograph; Infiltration (HVAC); Hydrology (agriculture); Environmental science; Surface runoff; Drainage; Drainage basin; Topographic Wetness Index; Precipitation; Water content; Soil science; Geology; Remote sensing; Geography; Meteorology; Digital elevation model","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0003430541,0.0004247082,0.0002043364,0.0006700637,0.0006002182,0.0006073068,0.0009843764,0.0003489817,0.0007153204],"category_scores_gemma":[0.0007236759,0.0002772773,0.0004638369,0.001105407,0.0003530606,0.0003375495,0.0003757652,0.0003453916,0.0001682769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007014479,"about_ca_system_score_gemma":0.005894077,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9513879,"about_ca_topic_score_gemma":0.9675915,"domain_scores_codex":[0.9998469,0.000009194348,0.000004862236,0.00004433604,0.00005293294,0.00004169882],"domain_scores_gemma":[0.9997297,0.00002698455,0.00002558503,0.00003100765,0.0001452193,0.00004146031],"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":[0.000172759,0.0001163844,0.3173346,0.00005547789,0.0002111663,0.0002804353,0.0003021625,0.6377184,0.004481441,0.0009593923,0.002380094,0.03598758],"study_design_scores_gemma":[0.0000346154,0.00002054942,0.251734,0.00001717738,0.00004303498,0.00003616568,0.0001701167,0.7434857,0.001453128,0.0001973929,0.002754084,0.00005401698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920661,0.0001185569,0.002613653,0.00006414758,0.000005001894,0.00002035737,0.003257705,0.0001993727,0.001655186],"genre_scores_gemma":[0.9940451,0.00006520231,0.002575986,0.000008339713,0.000001585842,0.000007189268,0.002883157,0.00001847192,0.0003950626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04861206,"threshold_uncertainty_score":0.09779662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03121464071542637,"score_gpt":0.1934743614706709,"score_spread":0.1622597207552445,"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."}}