{"id":"W2064991781","doi":"10.1007/s11157-005-4997-7","title":"Microbial Source Tracking for Identification of Fecal Pollution","year":2005,"lang":"en","type":"article","venue":"Reviews in Environmental Science and Bio/Technology","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Pollution; Fecal coliform; Source tracking; Sewage; Biology; Environmental science; Feces; Water quality; Ecology; Environmental engineering; 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":[0.001466295,0.00009619599,0.0001719941,0.0001608711,0.0001288372,0.00001448356,0.0002573328,0.00008974986,0.00007637421],"category_scores_gemma":[0.00009345794,0.00008193545,0.00003289775,0.0005508036,0.001373322,0.0003062024,0.0001601184,0.00007589403,0.00006435421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002864431,"about_ca_system_score_gemma":0.000006006576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008985056,"about_ca_topic_score_gemma":0.00003510612,"domain_scores_codex":[0.9987677,0.0000326647,0.0004254881,0.0003553221,0.0001894503,0.0002293445],"domain_scores_gemma":[0.9996089,0.00001032081,0.0001645314,0.0001721353,0.000003487672,0.00004067762],"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":[0.000003526115,0.00006519934,0.01461108,0.000008652277,4.433294e-7,7.654725e-8,0.0001035991,0.00001883019,0.5499187,0.0001137917,0.00002730822,0.4351288],"study_design_scores_gemma":[0.0007167017,0.0001633108,0.1424845,0.00006184966,0.00001686228,0.00001991131,0.000332673,0.002884319,0.6594222,0.0006815658,0.1928834,0.0003327149],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952285,0.0005978546,0.001770185,0.001785173,0.0000385883,0.0004861725,0.000006325427,0.00001404171,0.00007318873],"genre_scores_gemma":[0.997805,0.0006786749,0.001163499,0.0001736442,0.00001293025,0.00003013757,0.000002761224,0.000003816201,0.0001295667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4347961,"threshold_uncertainty_score":0.5060061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01835186755216112,"score_gpt":0.2720197616474472,"score_spread":0.2536678940952861,"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."}}