{"id":"W2467132508","doi":"10.1120/jacmp.v17i4.6117","title":"Physically constrained voxel‐based penalty adaptation for ultra‐fast IMRT planning","year":2016,"lang":"en","type":"article","venue":"Journal of Applied Clinical Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research","funders":"Cancer Research UK","keywords":"Voxel; Computer science; Radiation treatment planning; Adaptation (eye); Mathematical optimization; Process (computing); Workload; Algorithm; Artificial intelligence; Radiation therapy; Mathematics; Medicine; Radiology; Optics","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":[0.0005090262,0.0005119121,0.0003847532,0.0002885198,0.0003091714,0.0005723548,0.0009700006,0.0005698859,0.002564627],"category_scores_gemma":[0.001876976,0.0004001773,0.00046135,0.0003997232,0.0003218091,0.0004194901,0.000832449,0.0009873784,0.0007201956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004592485,"about_ca_system_score_gemma":0.001075703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002619116,"about_ca_topic_score_gemma":0.002906174,"domain_scores_codex":[0.9996594,0.0001187578,0.00001648083,0.00004099433,0.0001394893,0.0000248954],"domain_scores_gemma":[0.9994636,0.0002579001,0.00006520475,0.00008343617,0.0001014622,0.00002841974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009611922,0.00004785606,0.0004192042,0.00007287497,0.00003070345,0.0000689523,0.0001007786,0.859449,0.01835552,0.004182586,0.001312756,0.1158637],"study_design_scores_gemma":[0.000006825285,0.00001422628,0.0001121138,0.000002735273,0.000002965943,0.00002384752,0.00000545391,0.995207,0.002476472,0.0008847177,0.00125619,0.000007518131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007498343,0.0000439605,0.991015,0.00004053602,0.00001536181,0.00003314021,0.00001547846,0.0006127734,0.0007253345],"genre_scores_gemma":[0.2082236,0.00007120922,0.7891636,0.00006035488,0.00001504208,0.0001797918,0.0001256491,0.0004904377,0.001670253],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002619116,"threshold_uncertainty_score":0.008579552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04057599566922744,"score_gpt":0.3774837398897615,"score_spread":0.336907744220534,"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."}}