{"id":"W2083019863","doi":"10.4314/wsa.v33i2.49059","title":"Alternative methods in tracking sources of microbial contamination in waters","year":2009,"lang":"en","type":"article","venue":"Water SA","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Source tracking; Contamination; Environmental science; Environmental impact of pharmaceuticals and personal care products; Environmental remediation; Pollutant; Pollution; Water source; Fecal coliform; Biochemical engineering; Biology; Ecology; Water quality; Computer science; Water resource management; Engineering","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":[0.002300203,0.001032196,0.0007053464,0.005286963,0.0004856717,0.001684174,0.001009829,0.001900248,0.001951362],"category_scores_gemma":[0.002772709,0.0006729933,0.0006971814,0.003147411,0.001089281,0.001845335,0.001664435,0.001352471,0.001050032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005604666,"about_ca_system_score_gemma":0.0005053323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001476297,"about_ca_topic_score_gemma":0.004463705,"domain_scores_codex":[0.9967995,0.001127915,0.000134001,0.000554782,0.001259866,0.0001240196],"domain_scores_gemma":[0.9978731,0.000780782,0.0005965246,0.0002217066,0.0004572882,0.00007062299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007492665,0.0001652608,0.03297876,0.002424651,0.0001941144,0.0003842649,0.0007079167,0.002898836,0.7049266,0.005224816,0.0007440521,0.2486015],"study_design_scores_gemma":[0.00009104089,0.002501415,0.03916875,0.0008370128,0.0005646397,0.003252863,0.001194594,0.03207968,0.8528336,0.01046065,0.05667553,0.0003402555],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2536317,0.04125078,0.6826977,0.0009262642,0.0006325679,0.0006634343,0.002244408,0.00123896,0.0167141],"genre_scores_gemma":[0.3301405,0.02500406,0.6318899,0.0003653549,0.0002194151,0.0006686334,0.0005503405,0.0001010256,0.0110608],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005286963,"threshold_uncertainty_score":0.01216477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02661261425622378,"score_gpt":0.3149124955681019,"score_spread":0.2882998813118781,"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."}}