{"id":"W3112052149","doi":"10.1016/j.aca.2020.12.005","title":"Reverse transcription lesion-induced DNA amplification: An instrument-free isothermal method to detect RNA","year":2020,"lang":"en","type":"article","venue":"Analytica Chimica Acta","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Grand Challenges Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Alberta Innovates - Technology Futures; Alfred P. Sloan Foundation","keywords":"Loop-mediated isothermal amplification; Chemistry; RNA; DNA; Amplicon; Complementary DNA; Multiple displacement amplification; DNA ligase; Molecular biology; Reverse transcriptase; Ligase chain reaction; Biophysics; Computational biology; Polymerase chain reaction; Biochemistry; Biology; Gene; DNA extraction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009259785,0.001056098,0.000717337,0.0006239717,0.0004223339,0.000485299,0.001251644,0.000959437,0.001974192],"category_scores_gemma":[0.0009131577,0.0006724522,0.0008082126,0.0003243527,0.0006672385,0.0005054072,0.0005540293,0.00228506,0.002005248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004777347,"about_ca_system_score_gemma":0.0007653138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003524875,"about_ca_topic_score_gemma":0.001068378,"domain_scores_codex":[0.9984843,0.0002096315,0.00005593173,0.0005160874,0.0005949676,0.0001390447],"domain_scores_gemma":[0.9994639,0.0001897604,0.00008569746,0.0001012391,0.0001127755,0.00004662882],"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":[0.00003583527,0.00002085114,0.00006632644,0.00006048157,0.000004563858,0.00002066084,0.00002482147,0.00002893445,0.9953979,0.0001744924,0.0001134283,0.004051764],"study_design_scores_gemma":[0.000007885264,0.00007365133,0.0003486712,0.000005975656,0.0000170633,0.0001475621,0.00000674806,0.001064791,0.9957996,0.00007509143,0.002441248,0.00001177325],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1726739,0.00185367,0.8147972,0.0004520729,0.0003721329,0.0006106449,0.001174053,0.003474575,0.004591804],"genre_scores_gemma":[0.4325785,0.001694759,0.5379139,0.0005745205,0.0001752596,0.0009098795,0.00366958,0.0006911223,0.02179242],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001974192,"threshold_uncertainty_score":0.006604314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03921765131154879,"score_gpt":0.3089928406530524,"score_spread":0.2697751893415036,"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."}}