{"id":"W4409402564","doi":"10.1101/2025.04.11.25325702","title":"Peritoneal Metastasis Prediction in Gastric Cancer: A Machine Learning Approach","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Metastasis; Cancer; Computer science; Medicine; Artificial intelligence; Machine learning; 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":[0.003313885,0.0005429876,0.0005906623,0.001818886,0.0001553881,0.0008340719,0.0003355356,0.0004499839,0.0007284908],"category_scores_gemma":[0.007961201,0.0001200722,0.0006825296,0.000754139,0.0001866992,0.0004465473,0.0003847644,0.0005708786,0.0003162354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003329466,"about_ca_system_score_gemma":0.0003592144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00121344,"about_ca_topic_score_gemma":0.0009959039,"domain_scores_codex":[0.9989936,0.0006558507,0.00006518241,0.0001144499,0.000121017,0.00004998748],"domain_scores_gemma":[0.9969667,0.002308024,0.0002469997,0.0001245713,0.0002649068,0.00008893118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002380703,0.0004267324,0.5197981,0.0002744799,0.000606254,0.0001266365,0.000085246,0.1072375,0.003809799,0.0003716517,0.002633178,0.3622497],"study_design_scores_gemma":[0.0001309275,0.0009167501,0.1302271,0.0001184932,0.0002612995,0.0002459122,0.0001289856,0.8612819,0.003044907,0.002528636,0.001077935,0.00003713452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9270102,0.004629663,0.06357695,0.001340507,0.0001061464,0.0001013123,0.0010663,0.0004440654,0.001724816],"genre_scores_gemma":[0.9869187,0.0002778193,0.01197266,0.00005411241,0.00006097881,0.00002465751,0.0004739665,0.000008972016,0.0002080905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003313885,"threshold_uncertainty_score":0.01752573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02003794811638128,"score_gpt":0.3020259938091152,"score_spread":0.2819880456927339,"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."}}