{"id":"W73408484","doi":"","title":"Fuzzy Model: Time Dependent Dispersion in Rivers.","year":2009,"lang":"en","type":"article","venue":"Indian International Conference on Artificial Intelligence","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Dispersion (optics); Fuzzy logic; Computer science; Artificial intelligence; Physics; Optics","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":[0.0007061054,0.0004509806,0.0007775634,0.0005891198,0.0005780088,0.001313839,0.00182672,0.001851167,0.004248789],"category_scores_gemma":[0.00274078,0.0002855452,0.0006705617,0.00078007,0.0004099952,0.00143731,0.0005487838,0.001390486,0.0005172195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009181796,"about_ca_system_score_gemma":0.0008783931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02797035,"about_ca_topic_score_gemma":0.01786714,"domain_scores_codex":[0.9998034,0.00005400451,0.00001103287,0.00004825804,0.00005027873,0.00003295976],"domain_scores_gemma":[0.9993254,0.0003687921,0.00005612184,0.00004317921,0.0001565936,0.00004998854],"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":[0.00006866823,0.00004415928,0.001273727,0.00002878354,0.00004233667,0.0001057037,0.00006377733,0.9494155,0.0005656047,0.0318883,0.001820685,0.01468268],"study_design_scores_gemma":[0.000003381758,0.00000699444,0.0001138736,0.000002797275,0.000004874642,0.000009276109,0.000006998376,0.9959406,0.00004811214,0.003614533,0.0002454786,0.000003129402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1369596,0.001374344,0.839803,0.002112083,0.0004361128,0.0000642454,0.001011615,0.0004111951,0.01782783],"genre_scores_gemma":[0.9474552,0.000661351,0.0332175,0.0001107879,0.0001523895,0.00008009696,0.0004601119,0.00005061745,0.01781197],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02797035,"threshold_uncertainty_score":0.05561507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06283129012735406,"score_gpt":0.3021028151528228,"score_spread":0.2392715250254687,"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."}}