{"id":"W4403596788","doi":"10.1039/d4an00729h","title":"Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time","year":2024,"lang":"en","type":"article","venue":"The Analyst","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Institut TransMedTech; Institut de Valorisation des Données; Natural Sciences and Engineering Research Council of Canada; Fonds de Recherche du Québec - Santé; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Coronavirus disease 2019 (COVID-19); Saliva; Pandemic; Virology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Population; Outbreak; 2019-20 coronavirus outbreak; Computer science; Medicine; Pathology; Internal medicine","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":[0.0008147629,0.0008977315,0.0006576847,0.0006108374,0.000333038,0.0006823078,0.001047532,0.001029179,0.003109601],"category_scores_gemma":[0.001085177,0.0005039279,0.0005487054,0.0003038621,0.000396209,0.0007395297,0.0007571205,0.0008075914,0.001621704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002873829,"about_ca_system_score_gemma":0.0003744519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003882545,"about_ca_topic_score_gemma":0.0007649318,"domain_scores_codex":[0.9992256,0.0001419882,0.00003499165,0.0002217075,0.0003156961,0.00005999101],"domain_scores_gemma":[0.9994099,0.0002739821,0.0001025255,0.00005428713,0.0001179145,0.00004125641],"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":[0.0002752608,0.0001865172,0.003594608,0.0001579004,0.00004074771,0.0001113108,0.00007795731,0.0002832419,0.9633204,0.0002736033,0.001010677,0.03066762],"study_design_scores_gemma":[0.00005561091,0.00118859,0.007668003,0.00003343823,0.00007867062,0.0008578911,0.0001431331,0.02872772,0.9539887,0.0003231869,0.00685106,0.00008387824],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6902669,0.002113174,0.2895612,0.001231696,0.0007245692,0.0006658593,0.001727111,0.006659502,0.007050004],"genre_scores_gemma":[0.7819573,0.001005485,0.2064499,0.001079743,0.0002065407,0.000575536,0.0007165364,0.0002457895,0.007763035],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003109601,"threshold_uncertainty_score":0.01040268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01403022796939163,"score_gpt":0.3394702304386823,"score_spread":0.3254400024692907,"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."}}