{"id":"W2048404358","doi":"10.1007/s00253-010-2880-0","title":"Quantitative identification of fecal water pollution sources by TaqMan real-time PCR assays using Bacteroidales 16S rRNA genetic markers","year":2010,"lang":"en","type":"article","venue":"Applied Microbiology and Biotechnology","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of the Environment, Conservation and Parks; Ministry of Environment; University of Guelph","funders":"","keywords":"TaqMan; Biology; Feces; 16S ribosomal RNA; Polymerase chain reaction; Ribosomal RNA; Fecal coliform; Microbiology; Real-time polymerase chain reaction; Veterinary medicine; Bacteria; Gene; Water quality; Genetics; Ecology","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":[0.0003772567,0.0001393845,0.0001945741,0.00007378987,0.0001364379,0.00001034448,0.0001737123,0.0005351127,0.0002683471],"category_scores_gemma":[0.00001388289,0.0001074199,0.00002942223,0.00008881601,0.001348227,0.00004744779,0.0001618514,0.0002155819,0.0001266426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002896311,"about_ca_system_score_gemma":0.000004069761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000186294,"about_ca_topic_score_gemma":0.00008021669,"domain_scores_codex":[0.9989573,0.0000811007,0.0003135768,0.0003662342,0.00003683612,0.0002449801],"domain_scores_gemma":[0.9995931,0.00003263971,0.0001446288,0.0001883021,0.000008975696,0.00003229822],"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":[0.00005110222,0.00004204546,0.001676347,0.000006639867,0.00001335788,4.471291e-7,0.0001198883,0.000003261568,0.9949716,0.000750947,0.000135485,0.002228859],"study_design_scores_gemma":[0.0002605051,0.00008234812,0.01351921,0.000001912167,0.00001976339,0.00002273814,0.00009220573,0.0001493397,0.9839225,0.0005981872,0.001184789,0.0001465016],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975572,0.00001554004,0.001274119,0.0006288425,0.00006791484,0.0001913214,0.00004292529,0.00005203328,0.0001701216],"genre_scores_gemma":[0.9977305,0.00002597918,0.001947196,0.00007663255,0.00000641519,0.000006730408,0.00008536369,0.000008128527,0.000113049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01184286,"threshold_uncertainty_score":0.4967598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007004254970955523,"score_gpt":0.214167574944374,"score_spread":0.2071633199734185,"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."}}