{"id":"W4381234490","doi":"10.23880/aii-16000138","title":"Why and how should we use Artificial Intelligence, Machine Learning, and Deep Learning Approaches Differently on COVID-19 Coronavirus and Other Pathogens Research?","year":2021,"lang":"en","type":"article","venue":"Annals of Immunology & Immunotherapy","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Coronavirus; Artificial intelligence; Pandemic; Deep learning; Computer science; Virology; Biology; Medicine; Infectious disease (medical specialty); Outbreak","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03280945,0.001012084,0.0025962,0.002932165,0.001505974,0.00940719,0.002344927,0.005414627,0.00237612],"category_scores_gemma":[0.06286528,0.0005233744,0.0016886,0.001647966,0.005843639,0.01584163,0.002959311,0.01220461,0.002079481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002396165,"about_ca_system_score_gemma":0.005971557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008293688,"about_ca_topic_score_gemma":0.01165766,"domain_scores_codex":[0.9916524,0.004532713,0.0006046309,0.0009875271,0.001520265,0.0007024867],"domain_scores_gemma":[0.9554241,0.02491083,0.001984517,0.002779262,0.01137301,0.003528302],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008709486,0.0007891789,0.02642454,0.003406081,0.001839906,0.0002525438,0.001334234,0.003951372,0.004440543,0.09674822,0.1177366,0.7422059],"study_design_scores_gemma":[0.0006214116,0.0007575756,0.01545078,0.008493159,0.001135233,0.0006647124,0.004482119,0.01868753,0.003985556,0.7458167,0.1995099,0.0003953493],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.01152777,0.1050897,0.04074824,0.8255692,0.009154371,0.000112372,0.0002966909,0.0003128374,0.007188782],"genre_scores_gemma":[0.2588257,0.1460817,0.1901982,0.3687703,0.02778769,0.0004598118,0.0005514764,0.0005596824,0.006765468],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9671906,"threshold_uncertainty_score":0.173515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3940130370186398,"score_gpt":0.4338332151295712,"score_spread":0.03982017811093141,"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."}}