{"id":"W4399722597","doi":"10.32920/26052403.v1","title":"Automatic Diagnosis of Endometrial Cancer With Deep Learning","year":2024,"lang":"en","type":"preprint","venue":"","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Toronto Metropolitan University","funders":"","keywords":"Endometrial cancer; Artificial intelligence; Cancer; Computer science; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006015028,0.000747052,0.0005236781,0.001472188,0.0003281329,0.0009205412,0.0009751628,0.00104288,0.002015529],"category_scores_gemma":[0.002013266,0.0004747914,0.000798068,0.0006427009,0.0003482837,0.0006809394,0.001004792,0.0009725568,0.001218276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007639909,"about_ca_system_score_gemma":0.0009080972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005362235,"about_ca_topic_score_gemma":0.009001986,"domain_scores_codex":[0.999568,0.0000774877,0.0000255766,0.0001213676,0.000124543,0.00008295659],"domain_scores_gemma":[0.9995456,0.0001662441,0.00004188838,0.00008164964,0.0001326732,0.00003188688],"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":[0.0003378148,0.0001679658,0.005365324,0.0001709982,0.0001060605,0.0002719074,0.00008110562,0.08468096,0.03622314,0.003216141,0.01449016,0.8548883],"study_design_scores_gemma":[0.00001542875,0.0000415423,0.001341762,0.00001975947,0.00001912814,0.0001232614,0.00002285691,0.9813144,0.01037683,0.004357397,0.002355113,0.00001257326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1505655,0.004488944,0.8267366,0.00203273,0.0004312515,0.0002396932,0.001548654,0.006660408,0.007296275],"genre_scores_gemma":[0.6545581,0.001576521,0.3264367,0.0008124149,0.0002828288,0.0001536611,0.003612507,0.0002309537,0.01233636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005362235,"threshold_uncertainty_score":0.01066208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01940488521175625,"score_gpt":0.2793411020639954,"score_spread":0.2599362168522391,"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."}}