{"id":"W3041772724","doi":"10.1016/j.aca.2020.06.001","title":"Single universal primer recombinase polymerase amplification-based lateral flow biosensor (SUP-RPA-LFB) for multiplex detection of genetically modified maize","year":2020,"lang":"en","type":"article","venue":"Analytica Chimica Acta","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Biotechnology Research Institute","funders":"National Major Science and Technology Projects of China","keywords":"Recombinase Polymerase Amplification; Biosensor; Loop-mediated isothermal amplification; Multiplex ligation-dependent probe amplification; Chemistry; Multiplex; Primer (cosmetics); Recombinase; Molecular biology; Multiple displacement amplification; Genetically modified organism; Detection limit; Polymerase chain reaction; Multiplex polymerase chain reaction; DNA; Chromatography; Genetics; Biology; Gene; Biochemistry; Recombination; DNA extraction","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007408175,0.0002831014,0.0003810013,0.0001593541,0.00008960254,0.0000477277,0.0001891594,0.0002076564,0.00006960594],"category_scores_gemma":[0.0001979286,0.0002889496,0.0002790533,0.0004356429,0.000103555,0.00009955991,0.00002190863,0.000200826,0.00001952402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008198989,"about_ca_system_score_gemma":0.00003182116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001546161,"about_ca_topic_score_gemma":0.00001021877,"domain_scores_codex":[0.9984811,0.00004273722,0.0004868864,0.0004160785,0.000195011,0.0003782055],"domain_scores_gemma":[0.9989492,0.0002244984,0.00008791315,0.0003205614,0.0001277132,0.0002900754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002665656,0.0001384613,0.00002638982,0.00009695621,0.0001369058,0.000001821235,0.00006450198,0.003211746,0.993371,0.0001278381,0.0001476429,0.002410184],"study_design_scores_gemma":[0.0008088599,0.0001977494,0.0002887963,0.00001699141,0.000127912,0.000001028565,0.00001820692,0.6179942,0.3798262,0.00005186054,0.0004493701,0.0002187896],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775656,0.00001503865,0.01886253,0.001868521,0.0001555312,0.0005621641,0.0001750549,0.000393004,0.0004025168],"genre_scores_gemma":[0.9955479,0.00001262781,0.003904112,0.000181416,0.0001388617,0.00001116153,0.00007137424,0.00006574639,0.00006678616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6147825,"threshold_uncertainty_score":0.9999563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100642151169827,"score_gpt":0.2101099907256495,"score_spread":0.1891035692139512,"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."}}