{"id":"W3092071409","doi":"10.1093/clinchem/hvaa212","title":"Deus Ex Machina? Predicting SARS-CoV-2 Infection from Lab Tests Using Machine Learning","year":2020,"lang":"en","type":"article","venue":"Clinical Chemistry","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Electricity Association; University of Ottawa; Ottawa Hospital","funders":"","keywords":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Virology; Coronavirus Infections; Sars virus; Medicine; Internal medicine; Infectious disease (medical specialty)","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","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004589677,0.0002698474,0.0005864762,0.00002104901,0.000136344,0.00005100936,0.0001433292,0.0003893877,0.0001748533],"category_scores_gemma":[0.01092006,0.0002783724,0.0002756324,0.0002796811,0.000129955,0.00008528712,0.0002369654,0.001617495,0.00007806648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001656245,"about_ca_system_score_gemma":0.0002207108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007080923,"about_ca_topic_score_gemma":0.00001413782,"domain_scores_codex":[0.9976863,0.0001105471,0.0008127871,0.0007384878,0.000323975,0.0003278685],"domain_scores_gemma":[0.9976172,0.001299618,0.0003132108,0.000364489,0.0001070878,0.0002984333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001418621,0.0002077675,0.7945634,0.0002417752,0.00008677095,0.0001024362,0.00008375965,0.0001124173,0.2018515,2.158365e-7,0.001123415,0.001484692],"study_design_scores_gemma":[0.006129208,0.0004752245,0.1157606,0.001255455,0.0009670335,0.00008233373,0.00004446209,0.2534454,0.5506372,0.00005421323,0.07036346,0.0007854552],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909533,0.0002840864,0.0002615884,0.007288666,0.0002171561,0.0001603966,0.00002098167,0.0004845102,0.0003292819],"genre_scores_gemma":[0.9829457,0.00007180461,0.001341821,0.01317947,0.002193974,0.000005365526,0.0001296969,0.00007012315,0.0000619997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6788028,"threshold_uncertainty_score":0.9999669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1343326228294598,"score_gpt":0.4225643633082537,"score_spread":0.2882317404787939,"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."}}