{"id":"W4391636325","doi":"10.1055/s-0043-1776428","title":"Radiomics in Musculoskeletal Tumors","year":2024,"lang":"en","type":"article","venue":"Seminars in Musculoskeletal Radiology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sinai Health System; Women's College Hospital; University of Toronto; University Health Network; Mount Sinai Hospital","funders":"","keywords":"Radiomics; Medicine; Sarcoma; Radiogenomics; Medical imaging; Viewpoints; Medical physics; Radiology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001575334,0.0004387406,0.0009420016,0.001187259,0.00005539229,0.00003980785,0.0003133263,0.0003850089,0.0002632184],"category_scores_gemma":[0.0009396551,0.0003969048,0.000413264,0.001180315,0.0005295669,0.0001772935,0.0001222803,0.002071222,0.0001357699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004994657,"about_ca_system_score_gemma":0.0003002777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000152158,"about_ca_topic_score_gemma":0.00003587648,"domain_scores_codex":[0.9965529,0.0002946905,0.0008552286,0.0009497773,0.0003453452,0.001002006],"domain_scores_gemma":[0.9985914,0.000510251,0.00007092056,0.0004941863,0.00003058349,0.0003026724],"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":[0.0004601645,0.0007781564,0.2205213,0.003504109,0.0003454757,0.02162852,0.002621595,0.001580197,0.02282181,0.02127775,0.01215446,0.6923065],"study_design_scores_gemma":[0.01402808,0.004515532,0.3933674,0.01126134,0.0006022095,0.02410512,0.002148562,0.3438976,0.0004948197,0.01563299,0.1861598,0.003786639],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744871,0.01032229,0.0006037974,0.004359097,0.001311806,0.0005316737,0.000005496161,0.0002268238,0.008151878],"genre_scores_gemma":[0.9924873,0.001986897,0.003147305,0.0005461033,0.0006241129,0.00007889959,0.0001004643,0.0001077433,0.0009211361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6885198,"threshold_uncertainty_score":0.9998483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006774629798402162,"score_gpt":0.3064794987569897,"score_spread":0.2997048689585875,"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."}}