{"id":"W2013188904","doi":"10.1016/j.mimet.2011.12.005","title":"Quantitative real-time PCR (qPCR) detection chemistries affect enumeration of the Dehalococcoides 16S rRNA gene in groundwater","year":2011,"lang":"en","type":"article","venue":"Journal of Microbiological Methods","topic":"Microbial bioremediation and biosurfactants","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Strategic Environmental Research and Development Program; University of Toronto","keywords":"Amplicon; Melting curve analysis; Dehalococcoides; TaqMan; Molecular biology; SYBR Green I; 16S ribosomal RNA; Real-time polymerase chain reaction; Biomarker; Biology; Detection limit; Primer (cosmetics); Ribosomal RNA; Polymerase chain reaction; Gene; Chemistry; Microbiology; Chromatography; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001900456,0.0001239583,0.000265123,0.00003736168,0.00005285451,0.00001105612,0.000245077,0.0001440067,0.0009456383],"category_scores_gemma":[0.0003935983,0.0000666987,0.0001405823,0.0002311243,0.0002643737,0.0001248908,0.0000916531,0.0001945489,0.00002340451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000118987,"about_ca_system_score_gemma":0.00001356284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009733717,"about_ca_topic_score_gemma":0.00003860681,"domain_scores_codex":[0.9982808,0.0007800836,0.0005421168,0.0001454197,0.0000939395,0.0001576209],"domain_scores_gemma":[0.9991053,0.0001601909,0.0005473503,0.0001074084,0.00003715541,0.00004258707],"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":[0.0001704279,0.00009972751,0.01048255,0.000003520085,0.00001270307,0.000001959707,0.0003213334,0.000008889055,0.9844231,0.000003030184,0.000059764,0.004412972],"study_design_scores_gemma":[0.0002354266,0.0003169261,0.1300952,0.00001605938,0.00001463761,0.00003759815,0.00005117033,0.00001490257,0.8687796,0.0001920627,0.0001691406,0.00007725475],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996638,0.00004208757,0.002552353,0.0000524697,0.0001641559,0.0001337862,0.000005155913,0.000005185624,0.0004068018],"genre_scores_gemma":[0.9193126,0.0001049273,0.08044357,0.00004825137,0.00002152652,9.845191e-7,0.000001213774,0.000004546803,0.00006240578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1196126,"threshold_uncertainty_score":0.9999676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04582219723019299,"score_gpt":0.301313069753638,"score_spread":0.255490872523445,"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."}}