{"id":"W4288489840","doi":"10.3390/v14081667","title":"Novel Coronavirus and Common Pneumonia Detection from CT Scans Using Deep Learning-Based Extracted Features","year":2022,"lang":"en","type":"article","venue":"Viruses","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Prince Mohammad Bin Fahd University; Qassim University","keywords":"Coronavirus disease 2019 (COVID-19); Artificial intelligence; Machine learning; Pandemic; Pneumonia; Computer science; Support vector machine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Classifier (UML); Deep learning; Process (computing); Feature extraction; Medicine; Pattern recognition (psychology); Infectious disease (medical specialty); Disease; Pathology; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001649262,0.0002009809,0.000301558,0.0002056103,0.0005428176,0.00005826567,0.000091017,0.0000530272,0.0002239553],"category_scores_gemma":[0.0002315873,0.0002146573,0.00006186553,0.0003405895,0.00008526914,0.00009712165,0.0001046782,0.000598724,0.000005998945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003605714,"about_ca_system_score_gemma":0.000131377,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02207286,"about_ca_topic_score_gemma":0.002549283,"domain_scores_codex":[0.9986286,0.000137749,0.0002200424,0.0003967917,0.0003720973,0.0002446841],"domain_scores_gemma":[0.9988503,0.0005696292,0.0001491772,0.0002674488,0.00004395377,0.0001194643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004159409,0.0003569245,0.07054102,0.00003452793,0.00006502237,0.0001098611,0.000214678,0.0194131,0.887013,0.000002233532,0.00009796174,0.02173569],"study_design_scores_gemma":[0.003663377,0.000705913,0.6943119,0.0001682803,0.000492755,0.0002339776,0.0003385502,0.05524033,0.1378454,0.00002047777,0.1064817,0.0004973293],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963666,0.001083122,0.0007898957,0.0008475478,0.0002843744,0.000273106,0.00008806492,0.0002555433,0.00001174445],"genre_scores_gemma":[0.9878426,0.00002313131,0.0004412989,0.01140312,0.0001172196,0.00003854153,0.00005166631,0.00005874524,0.00002364609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7491676,"threshold_uncertainty_score":0.9844393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05791515849909522,"score_gpt":0.3361427818980977,"score_spread":0.2782276233990024,"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."}}