{"id":"W3175708866","doi":"10.1016/j.diagmicrobio.2021.115458","title":"Extractionless nucleic acid detection: a high capacity solution to COVID-19 testing","year":2021,"lang":"en","type":"article","venue":"Diagnostic Microbiology and Infectious Disease","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Multiplex; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); False positive paradox; Nucleic acid; Nucleic Acid Amplification Tests; Detection limit; 2019-20 coronavirus outbreak; Real-time polymerase chain reaction; Computational biology; Multiplex polymerase chain reaction; Genome; Virology; Biology; Gene; Polymerase chain reaction; Chromatography; Chemistry; Medicine; Bioinformatics; Computer science; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0001941634,0.000226222,0.0002921129,0.0001804856,0.0005686932,0.00004315802,0.00003888489,0.0001731201,0.0001413271],"category_scores_gemma":[0.02093931,0.0002354282,0.00008682293,0.0005182723,0.0001557159,0.00009390082,0.00007025615,0.0003221552,0.0001125565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002269591,"about_ca_system_score_gemma":0.0003250291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002250031,"about_ca_topic_score_gemma":0.0002975819,"domain_scores_codex":[0.9985602,0.0001719203,0.0002948205,0.0005621609,0.00006058992,0.0003502849],"domain_scores_gemma":[0.9976677,0.001217907,0.0001027755,0.0002596749,0.0002635677,0.0004883485],"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":[0.0001085088,0.0002792231,0.06756204,0.000149223,0.00005036951,0.0003174712,0.0000898421,0.00002101008,0.9272003,0.00007476674,0.0003054701,0.003841791],"study_design_scores_gemma":[0.003998693,0.0007241197,0.1388944,0.0002656681,0.0005769515,0.0103567,0.0001350588,0.0003087441,0.8268541,0.001025995,0.01612857,0.0007309451],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877518,0.0004526112,0.009087619,0.0007671711,0.0007506976,0.0004044342,0.00005413703,0.0003832963,0.0003482345],"genre_scores_gemma":[0.9871368,0.00001884751,0.0004672626,0.01189645,0.0002889423,0.00009560369,0.000042803,0.00002434623,0.00002896695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1003462,"threshold_uncertainty_score":0.9873077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03295532599995305,"score_gpt":0.2790148454394678,"score_spread":0.2460595194395147,"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."}}