{"id":"W2598131902","doi":"","title":"The City and the Stream: Impacts of Municipal Wastewater Effluent on the Riffle Food Web in the Speed River, Ontario","year":2011,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Effluent; Wastewater; Riffle; Sanitary sewer; Environmental science; Food waste; Environmental engineering; Water resource management; Hydrology (agriculture); Waste management; Engineering; STREAMS; Computer science; Computer network; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007582699,0.0001931098,0.000275794,0.00002198581,0.0005548318,0.0000370317,0.0007373904,0.0001564415,0.0001120416],"category_scores_gemma":[0.00003753594,0.00004957951,0.000198084,0.0001802735,0.00063446,0.00007516613,0.00009820278,0.0003918688,0.000002256852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006434091,"about_ca_system_score_gemma":0.00004207227,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4129179,"about_ca_topic_score_gemma":0.9142628,"domain_scores_codex":[0.9986203,0.0004443063,0.0001521328,0.0002344836,0.0002947729,0.0002539904],"domain_scores_gemma":[0.9990443,0.000350548,0.0002297017,0.0002239043,0.0001068405,0.00004470814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.005759762,0.0006434098,0.01414907,0.0001458591,0.0003700246,0.00001029242,0.9582164,0.00001538747,0.003587138,0.005084787,0.0009214021,0.01109645],"study_design_scores_gemma":[0.0005937089,0.0005896036,0.2202588,0.00005391816,0.00007220969,0.000002011034,0.7751835,0.00001644363,0.0007369829,0.001103653,0.001255574,0.0001336142],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940826,0.00009785764,2.377684e-9,0.004297763,0.000111114,0.0006247949,0.0000318684,0.000007537003,0.0007464973],"genre_scores_gemma":[0.9696813,0.0001411569,0.000002123746,0.00002598603,0.00002064404,9.181547e-7,0.00003589996,0.000001164067,0.03009082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5013449,"threshold_uncertainty_score":0.5909915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01678023755026315,"score_gpt":0.1895323682026016,"score_spread":0.1727521306523385,"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."}}