{"id":"W2885336116","doi":"10.2166/wh.2007.010b","title":"Pathogen and indicator variability in a heavily impacted watershed","year":2007,"lang":"en","type":"article","venue":"Journal of Water and Health","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of British Columbia; Regional Municipality of Waterloo; Institut National de la Recherche Scientifique; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Water Network","keywords":"Pathogen; Giardia; Cryptosporidium; Indicator bacteria; Biology; Watershed; Turbidity; Fecal coliform; Clostridium perfringens; Indicator organism; Veterinary medicine; Human pathogen; Coliphage; Water quality; Microbiology; Ecology; Environmental science; Feces; Escherichia coli; Bacteria; Bacteriophage","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":[0.0002327084,0.0001613318,0.0002760847,0.0006480245,0.0008758975,0.0007809827,0.0003194538,0.0002201218,0.0003036229],"category_scores_gemma":[0.0009753894,0.0001593804,0.00008863709,0.001747007,0.0005524913,0.0001916296,0.0004794388,0.0001924241,0.00005923718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004004823,"about_ca_system_score_gemma":0.0025038,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6796775,"about_ca_topic_score_gemma":0.7993619,"domain_scores_codex":[0.9995326,0.00004636671,0.00001846327,0.0001114595,0.0001748485,0.0001163467],"domain_scores_gemma":[0.9994086,0.00005781275,0.0001797819,0.00002213425,0.0002488884,0.00008282116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001310445,0.00004316713,0.9845708,0.00001210072,0.0000225492,0.0002815436,0.001007263,0.0004905342,0.008104327,0.00004557197,0.0001544364,0.005136645],"study_design_scores_gemma":[0.00000266241,0.00002935632,0.9981087,0.000001919081,0.000006110186,0.00004107738,0.0005318686,0.0004688056,0.0004384049,0.00001423938,0.0003529556,0.000003924915],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996409,0.00001520988,0.00006688057,0.000007005806,3.455242e-7,0.00000385536,0.0001117731,0.000002860829,0.0001510979],"genre_scores_gemma":[0.9990923,0.00003861557,0.0001886155,0.000009574546,0.000001156431,0.000005698258,0.0004185717,0.000001574314,0.0002437969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6796775,"threshold_uncertainty_score":0.6444179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02158595994627188,"score_gpt":0.3006909349801974,"score_spread":0.2791049750339256,"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."}}