{"id":"W1666856988","doi":"10.1118/1.4925761","title":"TU‐G‐303‐01: Radiomics: Quantitative Imaging in the Service of Improved Treatment Decision Making","year":2015,"lang":"en","type":"article","venue":"Medical Physics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Radiomics; Radiogenomics; Medical imaging; Medical physics; Medicine; Precision medicine; Artificial intelligence; Computer science; Machine learning; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009267847,0.001763837,0.001042893,0.00234238,0.001144417,0.006578646,0.002154556,0.006293847,0.09787184],"category_scores_gemma":[0.006343495,0.0007895849,0.0007593174,0.002123628,0.002410988,0.003954404,0.003084815,0.00486642,0.04472479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00192041,"about_ca_system_score_gemma":0.001627302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001570336,"about_ca_topic_score_gemma":0.00176321,"domain_scores_codex":[0.9972779,0.001055016,0.0001000543,0.0004734806,0.0007834896,0.0003100652],"domain_scores_gemma":[0.9953356,0.001460563,0.000242672,0.0004797466,0.001211464,0.001269992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003416698,0.00009081869,0.0004529207,0.0003285603,0.00002560203,0.0001903363,0.0002172656,0.0008351281,0.008293845,0.04454587,0.7886825,0.1559954],"study_design_scores_gemma":[0.0000555024,0.0001566347,0.001089916,0.0001781349,0.00001351018,0.0002843714,0.00008522986,0.002621331,0.004457571,0.01457555,0.9764099,0.00007237338],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.00763031,0.04301617,0.271836,0.08904307,0.07141422,0.001245172,0.0090401,0.0305784,0.4761966],"genre_scores_gemma":[0.07463672,0.02977511,0.1561425,0.02025795,0.04474676,0.00114599,0.01346623,0.01341899,0.6464097],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.09787184,"threshold_uncertainty_score":0.3274139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03087242155890867,"score_gpt":0.3560775288816501,"score_spread":0.3252051073227414,"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."}}