{"id":"W6520738","doi":"","title":"Dynamic Feedback Coupling of Continuous Hydrologic and Socio-Economic Model Components of the Upper Thames River Basin","year":2007,"lang":"en","type":"article","venue":"","topic":"Water resources management and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Baseflow; Hydrology (agriculture); Hydrological modelling; Groundwater recharge; Environmental science; Surface runoff; Streamflow; Structural basin; Water resources; Population; Land use; Land cover; Drainage basin; Precipitation; Water resource management; Geography; Groundwater; Climatology; Geology; Meteorology; Civil engineering; Aquifer; Cartography","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":[0.0001484706,0.0002719041,0.0002148605,0.0002373957,0.0003303999,0.0009404047,0.000364523,0.0003330669,0.002536641],"category_scores_gemma":[0.000749525,0.0002015819,0.000194203,0.0001831029,0.000436964,0.0004338264,0.0005453427,0.0003033882,0.0001150225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229285,"about_ca_system_score_gemma":0.0007165034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04224475,"about_ca_topic_score_gemma":0.02816126,"domain_scores_codex":[0.9999022,0.0000356424,0.000003546303,0.00001910681,0.00001049317,0.00002892864],"domain_scores_gemma":[0.9997894,0.00005798732,0.00004598212,0.00001017177,0.00003220504,0.0000642275],"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":[0.0004651145,0.0002368049,0.06622811,0.00005493163,0.000169222,0.0006166502,0.0003239267,0.8929689,0.01577906,0.01315419,0.002221912,0.007781221],"study_design_scores_gemma":[0.00004545718,0.0001081221,0.04470942,0.000003759294,0.00002956849,0.00003171256,0.0002934688,0.9512705,0.0005808329,0.002353676,0.0005543249,0.00001902891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993287,0.00001783617,0.003508679,0.0002060084,0.000008729949,0.00001227085,0.0001737444,0.00007689079,0.00270888],"genre_scores_gemma":[0.9994286,0.000009510413,0.0001653111,0.000005347863,0.000001292331,0.000006727128,0.00003178994,0.000002685136,0.0003486969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04224475,"threshold_uncertainty_score":0.08399773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007133375094677783,"score_gpt":0.1841731009488429,"score_spread":0.1770397258541651,"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."}}