{"id":"W3034158687","doi":"10.1101/2020.06.04.20122473","title":"FEAT: A Flexible, Efficient and Accurate Test for COVID-19","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Coronavirus disease 2019 (COVID-19); Test (biology); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Simple (philosophy); Point (geometry); Reliability engineering; Machine learning; Algorithm; Real-time computing; Mathematics; Engineering; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004124294,0.0003047355,0.000518538,0.0001772593,0.0001433034,0.00007059557,0.0001342909,0.0002297345,0.00002738957],"category_scores_gemma":[0.008339014,0.0002720309,0.0001600153,0.0002295981,0.00008836626,0.00001411694,0.0003091626,0.0005552581,0.00003980422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000116388,"about_ca_system_score_gemma":0.0004155122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005372949,"about_ca_topic_score_gemma":0.00000895479,"domain_scores_codex":[0.9983502,0.00003663129,0.0003672133,0.0007157443,0.0002389789,0.0002912356],"domain_scores_gemma":[0.9981771,0.0007838106,0.0002054166,0.0003986323,0.0001226539,0.0003123542],"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":[0.001694537,0.000948181,0.1728076,0.01788123,0.0007197913,0.0009905335,0.004557579,0.0009194061,0.7691428,0.0007145827,0.01349399,0.01612978],"study_design_scores_gemma":[0.01236511,0.001657032,0.02882475,0.001606459,0.001338655,0.001028568,0.0004640463,0.1482622,0.463238,0.002802466,0.3365367,0.001876049],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9671841,0.0006897924,0.01828207,0.008190065,0.0007840035,0.00191153,0.00009497884,0.0007483559,0.002115128],"genre_scores_gemma":[0.9856432,0.00002099853,0.002758935,0.01042225,0.0005065037,0.0002519315,0.00003236995,0.00006535299,0.0002984321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3230428,"threshold_uncertainty_score":0.9999732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1229444571646938,"score_gpt":0.3738560846967024,"score_spread":0.2509116275320086,"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."}}