{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003633825,0.0004369094,0.001473614,0.001507581,0.001030605,0.003001188,0.001293809,0.005216455,0.0196305],"category_scores_gemma":[0.01625544,0.0003243236,0.0009272811,0.0008973902,0.0022451,0.007191507,0.0007202685,0.006909879,0.0110516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001266625,"about_ca_system_score_gemma":0.003604127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008541455,"about_ca_topic_score_gemma":0.008673685,"domain_scores_codex":[0.9982064,0.0005106119,0.0002831826,0.0002492848,0.0005714425,0.0001790625],"domain_scores_gemma":[0.9888126,0.004325934,0.001150805,0.0003917772,0.003853468,0.001465443],"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":[0.0002318542,0.000103536,0.00449209,0.004671373,0.0001161188,0.0007016645,0.000335826,0.00009746446,0.0004454708,0.003620263,0.6928141,0.2923703],"study_design_scores_gemma":[0.00006966134,0.0001510335,0.003702631,0.008381412,0.0001449691,0.004388566,0.001625617,0.0001455556,0.0004587242,0.008695751,0.9721503,0.00008580503],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.002211205,0.357488,0.001241385,0.5791604,0.04221829,0.00006174514,0.001019576,0.0002071546,0.01639239],"genre_scores_gemma":[0.02762607,0.392174,0.003519589,0.4705189,0.09099967,0.0001338305,0.00137688,0.0001508007,0.01350021],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.0196305,"threshold_uncertainty_score":0.06567055,"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."}}