{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008184077,0.00008225448,0.0001419164,0.000080349,0.00001690202,0.00001412959,0.0001305037,0.00004504336,0.0002063299],"category_scores_gemma":[0.00001715148,0.0000601741,0.00003013049,0.00009519716,0.00005805746,0.000216755,0.0000401044,0.00008396097,0.00003229026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001192363,"about_ca_system_score_gemma":0.000001570058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009679934,"about_ca_topic_score_gemma":0.0002304035,"domain_scores_codex":[0.9989759,0.0002589707,0.0002813539,0.0001815426,0.0001185479,0.0001837394],"domain_scores_gemma":[0.9998138,0.00002672657,0.00004439036,0.00008397691,0.00000613437,0.0000250062],"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":[0.00005715968,0.0001983599,0.1563197,0.00001032274,0.000003727754,0.0000168739,0.02893728,0.0009147946,0.6912229,0.0001501695,0.00002295363,0.1221457],"study_design_scores_gemma":[0.0004413924,0.00004187509,0.3853378,0.00001232188,0.000001491321,0.000001033193,0.00009680889,0.0004934783,0.6119075,0.001280616,0.000308783,0.00007694346],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948052,0.000003540098,0.002865852,0.0004031086,0.00005943192,0.0001221744,0.000001159292,0.000009072012,0.001730447],"genre_scores_gemma":[0.9974828,0.000001513459,0.002006281,0.0002274798,0.000008838459,0.000002989071,0.000006316481,0.000003545189,0.0002602342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2290181,"threshold_uncertainty_score":0.2453829,"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."}}