{"id":"W7104183997","doi":"","title":"Hybrid ResNet-ViT Framework for Endometrial Lesion Analysis: A Comparative Study of MRI and CT in Endometrial Cancer Classification","year":2025,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Endometrial and Cervical Cancer Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Endometrial cancer; Obstetrics and gynaecology; Magnetic resonance imaging; Computed tomography; University hospital; Medical imaging; Medical record","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":[0.002172638,0.001122502,0.001214887,0.003571797,0.0004657764,0.001729095,0.001135157,0.001228326,0.001396448],"category_scores_gemma":[0.003946033,0.0002305823,0.001208238,0.001344881,0.0002294568,0.001326613,0.0009047079,0.0007318663,0.0007346398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006207142,"about_ca_system_score_gemma":0.001133845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01345673,"about_ca_topic_score_gemma":0.0173446,"domain_scores_codex":[0.9988157,0.0003209759,0.0001185019,0.0002706768,0.0003277645,0.0001464159],"domain_scores_gemma":[0.9988139,0.0005826237,0.00005730767,0.00008962004,0.0003278209,0.0001288357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002557651,0.001745468,0.1279355,0.0005708872,0.001220825,0.0009645107,0.0003006725,0.05587659,0.007696984,0.00100861,0.01202921,0.7880931],"study_design_scores_gemma":[0.0001121119,0.0009701466,0.03662409,0.0001561006,0.0006541053,0.0009227319,0.0005811364,0.9483415,0.004522596,0.001551723,0.005490673,0.00007322345],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8493118,0.01490677,0.1171518,0.001637192,0.0007342095,0.000597678,0.004301511,0.004156402,0.007202603],"genre_scores_gemma":[0.9241255,0.003204489,0.062373,0.0003452188,0.0003047423,0.000183669,0.007020188,0.000219581,0.002223712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01345673,"threshold_uncertainty_score":0.02675682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3998672757866111,"score_gpt":0.6109415350816719,"score_spread":0.2110742592950609,"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."}}