{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002240997,0.001500614,0.0008388674,0.001215679,0.0005301766,0.0007515692,0.001215459,0.001048612,0.002633873],"category_scores_gemma":[0.001899261,0.0007342814,0.001157734,0.000656835,0.0006362625,0.0006559929,0.0007870664,0.001144881,0.00234744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004999959,"about_ca_system_score_gemma":0.0008021188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004923341,"about_ca_topic_score_gemma":0.000837815,"domain_scores_codex":[0.9962985,0.001022585,0.0002127576,0.0006843117,0.001561643,0.0002202825],"domain_scores_gemma":[0.9988915,0.0002407394,0.0002428078,0.0001403428,0.0004132851,0.00007128094],"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":[0.0002313487,0.0001356905,0.001454504,0.0005212795,0.00002838805,0.0001087479,0.0001343086,0.0004666891,0.9780509,0.0004016127,0.0007278994,0.01773868],"study_design_scores_gemma":[0.00003586277,0.0005627638,0.002870243,0.00007002984,0.00005397817,0.0005328344,0.00004740015,0.007397317,0.9786163,0.0001941098,0.009543571,0.00007561568],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3318186,0.008419136,0.6390107,0.000564567,0.000659052,0.001065772,0.001760332,0.007249613,0.009452254],"genre_scores_gemma":[0.5480993,0.003306651,0.4246518,0.0004525367,0.0001362751,0.001797698,0.004398275,0.000431592,0.01672584],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002633873,"threshold_uncertainty_score":0.01185167,"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."}}