{"id":"W4246876597","doi":"10.5194/hessd-4-1301-2007","title":"GIBSI: an integrated modelling system for watershed management – sample applications and current developments","year":2007,"lang":"en","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Ministry of Environment; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Watershed; Environmental science; Watershed management; Water quality; Nonpoint source pollution; Environmental resource management; Water resource management; Hydrology (agriculture); Land use; Environmental planning; Current (fluid); Computer science; Engineering; Civil engineering; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.002083491,0.001107853,0.000798905,0.001352486,0.0003637662,0.001734977,0.002266995,0.0008247512,0.02036975],"category_scores_gemma":[0.002328516,0.0005727526,0.0006981655,0.002337936,0.0003760438,0.0013799,0.001461311,0.001157247,0.004884022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187665,"about_ca_system_score_gemma":0.001874938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02586684,"about_ca_topic_score_gemma":0.01931378,"domain_scores_codex":[0.99939,0.0001692157,0.00006209716,0.00008208841,0.0002465499,0.00005009653],"domain_scores_gemma":[0.999177,0.0002354979,0.00004860482,0.0001840742,0.0002443756,0.0001103573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001378979,0.0004190486,0.009551283,0.002028337,0.0003681931,0.0006948733,0.001125506,0.2139596,0.03674731,0.0395177,0.2216517,0.4725574],"study_design_scores_gemma":[0.0004916794,0.0002336114,0.006527869,0.0004367765,0.0001406614,0.0002797699,0.0001835055,0.5575176,0.01425362,0.01235996,0.4073416,0.0002333699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02461772,0.001078055,0.5629281,0.001297648,0.0002791293,0.001005952,0.03823533,0.3426726,0.02788546],"genre_scores_gemma":[0.1565057,0.003000423,0.6895862,0.0009881501,0.0001620899,0.002018946,0.1068848,0.02156505,0.01928864],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02586684,"threshold_uncertainty_score":0.06814355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0380159677697829,"score_gpt":0.2718933010937591,"score_spread":0.2338773333239763,"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."}}