{"id":"W3176287598","doi":"10.1038/s41598-021-92677-z","title":"A rapid near-patient detection system for SARS-CoV-2 using saliva","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services; University of British Columbia, Okanagan Campus; University of British Columbia; University of Calgary","funders":"Canadian Institutes of Health Research; Fast Grants; University of Calgary","keywords":"Saliva; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Virology; Sars virus; Coronavirus Infections; Betacoronavirus; Medicine; Computational biology; Biology; Outbreak; Infectious disease (medical specialty); Pathology; Internal medicine; Disease","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":[0.00127714,0.000623224,0.0007394109,0.0005989291,0.0003103246,0.0006237105,0.0006765943,0.0009219839,0.001390933],"category_scores_gemma":[0.0009715026,0.000361214,0.0006812162,0.0002862858,0.0002267779,0.0006109357,0.0008776427,0.0005601867,0.001061412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002652715,"about_ca_system_score_gemma":0.0005327427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000329527,"about_ca_topic_score_gemma":0.000420939,"domain_scores_codex":[0.9986247,0.0004519078,0.00007219156,0.0002551274,0.0005379897,0.00005816115],"domain_scores_gemma":[0.9995166,0.0001234587,0.00009100457,0.00003749931,0.0001964863,0.00003490634],"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":[0.0004469572,0.0001964167,0.005924908,0.0003267403,0.000045064,0.0001317818,0.0002010274,0.0002889758,0.9282759,0.0002458786,0.0008520966,0.06306417],"study_design_scores_gemma":[0.0001241132,0.004233842,0.02000643,0.000112456,0.0002480878,0.004197612,0.0002783963,0.01792143,0.9342005,0.0002766091,0.01821122,0.0001894602],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6216775,0.005521799,0.3559522,0.0007483562,0.0003991532,0.001671546,0.002832398,0.006407439,0.004789644],"genre_scores_gemma":[0.6646918,0.002123893,0.324795,0.0009992912,0.0001241207,0.0009261988,0.001894634,0.0001368445,0.004308349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001390933,"threshold_uncertainty_score":0.00675422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06751985180645685,"score_gpt":0.3108324503182676,"score_spread":0.2433125985118108,"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."}}