{"id":"W4410081416","doi":"10.1061/joeedu.eeeng-8104","title":"Rethinking TMDLs: Perspective Based on Community Survey","year":2025,"lang":"en","type":"article","venue":"Journal of Environmental Engineering","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Perspective (graphical); Environmental planning; Water quality; Environmental science; Environmental engineering; Environmental resource management; Sociology; Water resource management; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008117018,0.00009434386,0.0001551442,0.0001616804,0.00008118258,0.00004445472,0.0005628717,0.00004120283,0.000007364944],"category_scores_gemma":[0.0002264977,0.00008326791,0.00007241539,0.00012049,0.00002356177,0.000178252,0.0001093585,0.0004668981,0.000002642183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002525862,"about_ca_system_score_gemma":0.00002349852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002888367,"about_ca_topic_score_gemma":0.000003517826,"domain_scores_codex":[0.9992987,0.0001134774,0.0001956722,0.00007696082,0.0001918702,0.0001233445],"domain_scores_gemma":[0.9991202,0.0004941425,0.00008599911,0.0002523096,0.00001180298,0.000035549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002438061,0.001874677,0.0683886,0.0001366649,0.000547003,0.000379699,0.010933,0.8142769,0.04363435,0.0337473,0.001182938,0.02465504],"study_design_scores_gemma":[0.0006792347,0.0002844804,0.8167421,0.0002048348,0.00001359682,0.00002544234,0.0004373922,0.1747585,0.005028915,0.001448437,0.0001944072,0.0001826052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.481629,0.0004013399,0.5149038,0.0005711589,0.0007837775,0.00006153609,0.000002655072,0.00004668458,0.001600064],"genre_scores_gemma":[0.9883034,0.00001425324,0.01144069,0.0001992027,0.00001879161,4.669747e-7,2.969153e-7,0.000004176811,0.00001867626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7483535,"threshold_uncertainty_score":0.3395567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01852344610081209,"score_gpt":0.2332163915651297,"score_spread":0.2146929454643176,"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."}}