{"id":"W2332523707","doi":"10.14796/jwmm.r235-01","title":"The Use of Decision Analysis and Watershed Modeling to Investigate E.coli Potential Sources and Solutions in Lake Tuscaloosa Watershed, Alabama","year":2009,"lang":"en","type":"article","venue":"Journal of Water Management Modeling","topic":"Water resources management and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Alabama","keywords":"Watershed; Environmental science; Hydrology (agriculture); Water resource management; Geology; Computer science; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006435709,0.0001958968,0.0003201347,0.000993307,0.0001519178,0.0003205673,0.0001954832,0.00005191566,0.000003543501],"category_scores_gemma":[0.000009154455,0.0001250821,0.0001045986,0.0003357361,0.00002493915,0.0005453537,0.0001615374,0.0001431573,9.959832e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003210522,"about_ca_system_score_gemma":0.000001685631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001816747,"about_ca_topic_score_gemma":0.0000891923,"domain_scores_codex":[0.9982976,0.00004619722,0.0007784013,0.000183248,0.0003234641,0.0003710575],"domain_scores_gemma":[0.9995425,0.00001489053,0.00007212735,0.0001772886,0.00007931764,0.0001138902],"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":[0.00008081763,0.00001652285,0.0003463737,0.00003264038,0.0002829932,0.00001902035,0.001258124,0.9929183,0.0006441188,0.00002089963,0.0000308166,0.004349386],"study_design_scores_gemma":[0.0005497988,0.0000470236,0.0003750617,0.00008554605,0.0004291298,0.000003628116,0.0002248545,0.9966556,0.0003116284,0.0009134298,0.0002462711,0.000158007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6123425,0.0000839879,0.3869818,0.0003782536,0.00004600574,0.0001355672,0.000001133315,0.000016006,0.00001480085],"genre_scores_gemma":[0.9846576,0.0006281867,0.01452891,0.00006549614,0.00003841711,0.000002790228,0.000009165624,0.00001767495,0.00005172853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3724529,"threshold_uncertainty_score":0.5100701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259102007219595,"score_gpt":0.200269052849205,"score_spread":0.177678032777009,"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."}}