{"id":"W3121590924","doi":"10.3389/fmed.2021.729287","title":"COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 From Chest CT Images Through Bigger, More Diverse Learning","year":2022,"lang":"en","type":"article","venue":"Frontiers in Medicine","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hamilton Health Sciences; McMaster University; Niagara Health System; University of Waterloo","funders":"Frederick National Laboratory for Cancer Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canadian Institute for Advanced Research","keywords":"Artificial intelligence; Leverage (statistics); Deep learning; Cohort; Computer science; Coronavirus disease 2019 (COVID-19); Artificial neural network; Benchmark (surveying); Machine learning; Medical physics; Clickstream; Medicine; Radiology; Geography; The Internet; Cartography; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001012554,0.001174041,0.0004787598,0.0006064143,0.000303232,0.0007519489,0.001554998,0.001029643,0.001943145],"category_scores_gemma":[0.003720135,0.0003417452,0.000651815,0.0004891737,0.0004001096,0.001079958,0.001441843,0.001787253,0.0006942331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001027592,"about_ca_system_score_gemma":0.001316008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009509515,"about_ca_topic_score_gemma":0.02065204,"domain_scores_codex":[0.9996234,0.00007832795,0.00002707267,0.0001223638,0.00007984373,0.00006898896],"domain_scores_gemma":[0.9992881,0.0002596201,0.00008830568,0.0001106066,0.000174061,0.00007934066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001267216,0.000847913,0.05345875,0.0004438603,0.0004202503,0.0007845808,0.0001873631,0.4801653,0.0184782,0.005214315,0.06106287,0.3776694],"study_design_scores_gemma":[0.00004823801,0.0001643152,0.003041089,0.00003546266,0.00003259878,0.0001396428,0.00002803723,0.9844986,0.006134585,0.002528974,0.003324487,0.00002391599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5123159,0.003143735,0.44003,0.004037953,0.0007512117,0.0006144511,0.01332224,0.01121853,0.01456592],"genre_scores_gemma":[0.8080864,0.0007030993,0.1564147,0.001928202,0.0001679859,0.0004145891,0.02350205,0.0002980118,0.008485066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009509515,"threshold_uncertainty_score":0.01890832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02623701137377057,"score_gpt":0.3202239473200387,"score_spread":0.2939869359462681,"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."}}