{"id":"W4400257668","doi":"10.1007/s00521-024-10053-0","title":"Res-MGCA-SE: a lightweight convolutional neural network based on vision transformer for medical image classification","year":2024,"lang":"en","type":"article","venue":"Neural Computing and Applications","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Convolutional neural network; Computer science; Transformer; Artificial intelligence; Artificial neural network; Pattern recognition (psychology); Computer vision; Engineering; Voltage; Electrical engineering","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":[0.0006751672,0.001084504,0.0008575264,0.001057224,0.0003254197,0.0007145372,0.00167831,0.0009870882,0.007134499],"category_scores_gemma":[0.001404461,0.000480954,0.0009503251,0.0007464148,0.0002831384,0.0008741932,0.001232804,0.001368163,0.00376051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005410268,"about_ca_system_score_gemma":0.001545466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008604363,"about_ca_topic_score_gemma":0.01810174,"domain_scores_codex":[0.9997225,0.00003983354,0.00001596308,0.00007792635,0.0001022807,0.00004144929],"domain_scores_gemma":[0.9996984,0.00006749398,0.00002173506,0.00008385915,0.0001020612,0.00002653396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003147213,0.0001855921,0.0009664749,0.0001626361,0.000216246,0.0001090397,0.00002344072,0.02123349,0.03292735,0.003874932,0.0234349,0.9165512],"study_design_scores_gemma":[0.00004648344,0.0001532292,0.001159756,0.00002864193,0.00008272184,0.000337142,0.00001447557,0.9387408,0.04137207,0.004617782,0.0134152,0.00003153992],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009838265,0.001082624,0.9719216,0.0002247867,0.0002203537,0.0001776641,0.0008036542,0.01356705,0.002164058],"genre_scores_gemma":[0.218404,0.001154763,0.758258,0.0007667384,0.0001872023,0.0003414493,0.004315531,0.001067264,0.01550504],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008604363,"threshold_uncertainty_score":0.02386725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03260923855441203,"score_gpt":0.3673986830672115,"score_spread":0.3347894445127995,"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."}}