{"id":"W4401282853","doi":"10.1038/s41598-024-69119-7","title":"Comparative analysis of vision transformers and convolutional neural networks in osteoporosis detection from X-ray images","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"AI in cancer detection","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Osteoporosis; Pattern recognition (psychology); Computer vision; Medicine; Pathology","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":[],"consensus_categories":[],"category_scores_codex":[0.003986208,0.0009192007,0.0006448692,0.001712978,0.0002454657,0.000891896,0.0006432931,0.0009962389,0.001044545],"category_scores_gemma":[0.01350203,0.0002334116,0.0004293306,0.0006711927,0.0004432835,0.00159923,0.0006579959,0.0005486894,0.0002848643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009767751,"about_ca_system_score_gemma":0.0006117469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005983222,"about_ca_topic_score_gemma":0.006443162,"domain_scores_codex":[0.9987174,0.0004017326,0.00009327925,0.0002429336,0.0003385916,0.000206123],"domain_scores_gemma":[0.9948485,0.003706994,0.000274494,0.0002455796,0.0007650267,0.0001593043],"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":[0.005268765,0.00121343,0.02937956,0.001205924,0.0005468034,0.0004286058,0.0003369238,0.2499114,0.04496781,0.00384032,0.002749444,0.6601511],"study_design_scores_gemma":[0.00003766693,0.001269993,0.01123614,0.00005511362,0.0001610114,0.0001514989,0.0001833085,0.9629861,0.02169572,0.001379915,0.0008154102,0.00002828461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9116594,0.004066638,0.07458056,0.0005862414,0.0001706239,0.0002563594,0.0003705683,0.00108415,0.007225459],"genre_scores_gemma":[0.9680729,0.0008486584,0.02900201,0.00007459457,0.00003349503,0.00004350481,0.0004077939,0.00004170042,0.001475353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005983222,"threshold_uncertainty_score":0.02108133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129677272911845,"score_gpt":0.2673122503732844,"score_spread":0.2560154776441659,"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."}}