{"id":"W2143223453","doi":"10.1128/aem.02112-05","title":"Direct Quantitation and Detection of Salmonellae in Biological Samples without Enrichment, Using Two-Step Filtration and Real-Time PCR","year":2006,"lang":"en","type":"article","venue":"Applied and Environmental Microbiology","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":141,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Public Safety Research and Treatment","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Filtration (mathematics); Chromatography; Salmonella; Detection limit; Sample preparation; Filter (signal processing); Biology; Real-time polymerase chain reaction; Extraction (chemistry); DNA extraction; Microbiology; Chemistry; Bacteria; Polymerase chain reaction; Mathematics; Gene; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001735008,0.0001343642,0.0002566315,0.00001994379,0.0000754561,0.000007755845,0.00003413198,0.0001436474,0.00002145268],"category_scores_gemma":[0.00000479555,0.00006702928,0.00001949088,0.00005244725,0.0002537621,0.00003456102,0.00005027111,0.00005042635,0.000003788163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001873782,"about_ca_system_score_gemma":0.000001008179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001184789,"about_ca_topic_score_gemma":0.0003174476,"domain_scores_codex":[0.9991183,0.0001083942,0.0002496726,0.0003260268,0.00001960866,0.0001779849],"domain_scores_gemma":[0.9996268,0.0002007092,0.0001126444,0.00002955125,0.000002009876,0.00002835719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004598879,0.0000317982,0.2219241,0.000002516174,0.00000426738,3.211682e-7,0.00001792138,0.00000518474,0.7741109,0.00005632801,0.00000198603,0.0037987],"study_design_scores_gemma":[0.0004833888,0.0002169248,0.9321414,0.000005752732,0.00001428473,0.0000464248,0.0002506395,0.0001468336,0.06590163,0.0004007328,0.0002247272,0.0001672319],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992114,0.0003161122,0.00001937439,0.00002049067,0.00001883316,0.0001855203,0.00005300323,0.00001340518,0.0001618353],"genre_scores_gemma":[0.9987753,0.0005659675,0.0003205946,0.00003400187,0.00003955876,0.000008396792,0.0002493346,0.000001272229,0.000005569178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7102174,"threshold_uncertainty_score":0.2733375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01671632391787875,"score_gpt":0.2086093077558644,"score_spread":0.1918929838379856,"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."}}