{"id":"W3201304018","doi":"10.1016/j.ijid.2021.09.015","title":"WarmStart colorimetric loop-mediated isothermal amplification for the one-tube, contamination-free and visualization detection of Shigella flexneri","year":2021,"lang":"en","type":"article","venue":"International Journal of Infectious Diseases","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University of Toronto","funders":"National Key Research and Development Program of China; Key Technologies Research and Development Program; Sichuan Province Science and Technology Support Program; Department of Science and Technology of Sichuan Province","keywords":"Shigella flexneri; Loop-mediated isothermal amplification; Plasmid; Shigella; Microbiology; Serial dilution; Medicine; Biology; Gene; DNA; Escherichia coli; Genetics","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":[0.0001581994,0.0000927411,0.000148947,0.0002345621,0.0000690716,0.00006747889,0.0001137282,0.00006093486,0.00003310028],"category_scores_gemma":[0.000852425,0.00007825642,0.0001106132,0.0002864155,0.00004807618,0.0001856223,0.0000181366,0.00009669158,0.000001426228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010184,"about_ca_system_score_gemma":0.00003798094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000116808,"about_ca_topic_score_gemma":0.00003604721,"domain_scores_codex":[0.9991018,0.00004232759,0.000392254,0.00008793276,0.0002906664,0.00008507953],"domain_scores_gemma":[0.9980945,0.0005150955,0.0001969223,0.00008831068,0.001048789,0.00005637999],"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":[0.0009543129,0.001582515,0.04645306,0.0005894817,0.004105418,0.0000261486,0.000644834,0.03209533,0.7099596,0.008125753,0.001582455,0.1938812],"study_design_scores_gemma":[0.006390556,0.0008997165,0.2979429,0.0002499231,0.000892426,0.0002668328,0.0006200963,0.2467084,0.4315706,0.0053936,0.008498118,0.0005668168],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7951011,0.001609,0.201339,0.0002480179,0.0012594,0.00016564,0.0001001188,0.00005391509,0.0001237538],"genre_scores_gemma":[0.9987527,0.0007542576,0.00004758771,0.00005666229,0.0003033855,0.000008469582,0.0000183234,0.00001670912,0.00004190434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2783889,"threshold_uncertainty_score":0.3191204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009092026749537333,"score_gpt":0.2416966016498435,"score_spread":0.2326045749003061,"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."}}