{"id":"W2058469538","doi":"10.1120/jacmp.v10i4.3055","title":"The effect of interfraction prostate motion on IMRT plans: a dose‐volume histogram analysis using a Gaussian error function model","year":2009,"lang":"en","type":"article","venue":"Journal of Applied Clinical Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Grand River Hospital; Princess Margaret Cancer Centre; University Health Network; Toronto Metropolitan University; University of Toronto; University of Waterloo","funders":"","keywords":"Isocenter; Prostate; Nuclear medicine; Mathematics; Histogram; Medicine; Gaussian; Volume (thermodynamics); Computer science; Physics; Imaging phantom; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.001419331,0.0002012444,0.000682862,0.00008846188,0.0001170252,0.00002438723,0.0002469429,0.0001297252,0.00002377883],"category_scores_gemma":[0.00006222863,0.0001251705,0.0006181917,0.000383376,0.0001748844,0.0001400434,0.00001738356,0.0009840376,0.000001165783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009338879,"about_ca_system_score_gemma":0.0000810804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005279003,"about_ca_topic_score_gemma":5.083337e-7,"domain_scores_codex":[0.9975843,0.0001459209,0.001153812,0.0002106266,0.0006896286,0.0002157067],"domain_scores_gemma":[0.9976804,0.000482785,0.001289454,0.0002656481,0.00009612145,0.000185623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004487251,0.0007062308,0.009705567,0.00001426153,0.001223973,0.000002452641,0.0001046399,0.02932746,0.001393569,0.003462586,0.0002990393,0.949273],"study_design_scores_gemma":[0.006503759,0.01095453,0.01042698,0.0003625973,0.003378774,0.000004983688,0.0001052083,0.8522834,0.005170496,0.1088171,0.001365129,0.0006270889],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2344793,0.00001710941,0.7644814,0.0002374104,0.0001658481,0.0002310352,0.000004917476,0.00002029187,0.0003627045],"genre_scores_gemma":[0.9952111,0.00002662694,0.003745882,0.0001355278,0.0008356199,0.00000726605,0.000006788239,0.00001776497,0.0000133884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9486459,"threshold_uncertainty_score":0.5104305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02039892200620455,"score_gpt":0.3637031680328762,"score_spread":0.3433042460266716,"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."}}