{"id":"W4317722176","doi":"10.1503/cmaj.1096034","title":"What to know about Omicron XBB.1.5","year":2023,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Strain (injury); China; Virology; Computer science; Medicine; Political science; Outbreak; Pathology; Disease; Anatomy; Infectious disease (medical specialty)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002262866,0.0001353451,0.0002940944,0.0006100038,0.0002644392,0.0002646482,0.0002017702,0.0003735739,0.003578082],"category_scores_gemma":[0.006631835,0.0001326004,0.0001380435,0.0008683226,0.00002463556,0.000197703,0.0000302612,0.0008892448,0.003985858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003179915,"about_ca_system_score_gemma":0.005294206,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002016023,"about_ca_topic_score_gemma":0.02521635,"domain_scores_codex":[0.9970191,0.0001177413,0.0004205817,0.0002226848,0.001487514,0.0007324225],"domain_scores_gemma":[0.9951997,0.0003966589,0.0001250705,0.0001659325,0.000422869,0.003689787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007190291,0.00001781827,0.0174792,0.00001226782,0.00005699026,0.0008496972,0.0004871073,0.00001332722,0.00007101391,0.0000286688,0.9177936,0.06318316],"study_design_scores_gemma":[0.0007965201,0.0000667092,0.06666145,0.0006043112,0.00003460643,0.0001819472,0.0003949569,0.0001704816,0.00006684239,0.0000520869,0.9308422,0.0001279456],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.1861351,0.0003912388,0.00002417628,0.8092901,0.003500715,0.0001924567,0.00001293044,0.00008739308,0.0003659181],"genre_scores_gemma":[0.1726418,0.004154527,0.0002256903,0.8004743,0.008388726,0.00003584101,0.00005987138,0.00010018,0.01391913],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06305521,"threshold_uncertainty_score":0.9973328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01316398115422126,"score_gpt":0.3017893354584024,"score_spread":0.2886253543041812,"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."}}