{"id":"W3033259525","doi":"10.18280/isi.250203","title":"COVID-19, Bacille Calmette-Guérin (BCG) and Tuberculosis: Cases and Recovery Previsions with Deep Learning Sequence Prediction","year":2020,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Sequence (biology); Tuberculosis; Virology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Medicine; Sequence learning; Mycobacterium tuberculosis; Microbiology; Biology; Artificial intelligence; Computer science; Internal medicine; Genetics; Pathology; Infectious disease (medical specialty); Outbreak","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":[],"consensus_categories":[],"category_scores_codex":[0.0003297295,0.0002279656,0.0003286572,0.0002111682,0.0004391367,0.0001925308,0.0000583974,0.0001303852,0.00005946791],"category_scores_gemma":[0.005887543,0.0002006899,0.00004339128,0.000449088,0.0002335125,0.00180835,0.00008482578,0.0002823281,0.0000177751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004655523,"about_ca_system_score_gemma":0.0003166251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003714169,"about_ca_topic_score_gemma":0.00003133775,"domain_scores_codex":[0.9985721,0.00009784035,0.0004870594,0.0002663674,0.0003210698,0.0002555347],"domain_scores_gemma":[0.9983569,0.0005124489,0.0002272498,0.0001753744,0.0001793912,0.0005486446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002764422,0.0001881517,0.361024,0.02132065,0.0007730883,0.0004064641,0.08099063,0.0328172,0.002905874,0.0007155619,0.009225894,0.4868681],"study_design_scores_gemma":[0.01553725,0.01552161,0.2330867,0.007890076,0.002276279,0.009571954,0.02486299,0.3188285,0.003093226,0.0007012137,0.3658662,0.002764012],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9718834,0.00100371,0.01420947,0.01067814,0.00008031724,0.001063199,0.00007188716,0.0005287839,0.0004810512],"genre_scores_gemma":[0.9833983,0.0008084562,0.001474899,0.01394349,0.00007996873,0.00009195484,0.0001676629,0.00002131882,0.00001399266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.484104,"threshold_uncertainty_score":0.8183895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0338992297906429,"score_gpt":0.2799560116419135,"score_spread":0.2460567818512706,"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."}}