{"id":"W2022280107","doi":"10.1118/1.4866219","title":"Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer","year":2014,"lang":"en","type":"article","venue":"Medical Physics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cancer Care Ontario; Western University","funders":"","keywords":"SABR volatility model; Ablative case; Radiation therapy; Radiosurgery; Medicine; Lung cancer; Radiology; Stereotactic radiotherapy; Medical imaging; Nuclear medicine; Medical physics; Oncology; Mathematics","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":[0.0004085431,0.0002528623,0.0002690386,0.0008410665,0.0001388687,0.0003050198,0.0001873762,0.000252735,0.0004489252],"category_scores_gemma":[0.002198049,0.0001177695,0.0002490097,0.0002681659,0.0001759887,0.0001815863,0.0001929674,0.0001961853,0.000146748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002512117,"about_ca_system_score_gemma":0.0001348551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001610495,"about_ca_topic_score_gemma":0.001795634,"domain_scores_codex":[0.9998143,0.00004294008,0.00002055581,0.00003375304,0.00006151381,0.0000270216],"domain_scores_gemma":[0.9990626,0.0002964254,0.000370138,0.00005415934,0.0001339032,0.00008282281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001054203,0.00009945917,0.9655833,0.00002335169,0.0000423156,0.0001852766,0.00006552981,0.001248097,0.007752591,0.000009752071,0.0001132331,0.0238229],"study_design_scores_gemma":[0.00001375778,0.0004327042,0.9880133,0.000004359089,0.00003393682,0.0009857219,0.00004392786,0.00696635,0.003351521,0.0000199819,0.000127657,0.000006799291],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989778,0.0001219691,0.0007277135,0.000009291655,0.000001931758,0.00001025842,0.00003529714,0.00001808496,0.00009774924],"genre_scores_gemma":[0.999456,0.00002325896,0.0003895535,0.000002712109,0.000002812332,0.000004039332,0.00007430612,0.000002527086,0.00004474598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001610495,"threshold_uncertainty_score":0.00320226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026204065219425,"score_gpt":0.3007954426123658,"score_spread":0.2905334019601715,"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."}}