{"id":"W4378349117","doi":"10.3390/curroncol30050372","title":"Radiomics and Radiogenomics in Pelvic Oncology: Current Applications and Future Directions","year":2023,"lang":"en","type":"review","venue":"Current Oncology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Radiogenomics; Radiomics; Medicine; Precision medicine; Medical physics; Bioinformatics; Intensive care medicine; Internal medicine; Pathology; Radiology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0007751339,0.0004665358,0.002393108,0.0008165648,0.000160849,0.00003197426,0.0001866904,0.0005486006,0.00001677335],"category_scores_gemma":[0.0001829084,0.0004053867,0.0002418115,0.0007109519,0.0003848774,0.00004001317,0.0002170172,0.002612319,0.00004101592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041151,"about_ca_system_score_gemma":0.001121996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001110629,"about_ca_topic_score_gemma":0.00002363636,"domain_scores_codex":[0.9973352,0.000325362,0.0009076413,0.000797512,0.000151841,0.0004824322],"domain_scores_gemma":[0.9980868,0.0006601042,0.0004088088,0.0003691155,0.00005711354,0.0004181261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001004673,0.0002891838,0.000222338,0.00934097,0.0001033953,0.00003562248,0.0002253747,2.653219e-7,2.391017e-7,0.000626981,0.001537019,0.9876086],"study_design_scores_gemma":[0.001119433,0.0001526363,0.0001638804,0.00266353,0.001229833,0.0009676968,0.00007254795,0.0003942377,1.41922e-8,0.0001679217,0.9927598,0.0003085221],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00009212596,0.9928879,0.0001560562,0.001377574,0.002978668,0.001874329,0.00005102843,0.0001241133,0.0004581897],"genre_scores_gemma":[0.000001981785,0.9949825,0.0005976754,0.00005934166,0.002986832,0.0007899266,0.0004128526,0.00009560712,0.00007331298],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9912227,"threshold_uncertainty_score":0.9998398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1040393706257472,"score_gpt":0.4646348769699741,"score_spread":0.3605955063442269,"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."}}