{"id":"W1864883322","doi":"10.1120/jacmp.v16i1.5089","title":"Margin selection to compensate for loss of target dose coverage due to target motion during external‐beam radiation therapy of the lung","year":2015,"lang":"en","type":"article","venue":"Journal of Applied Clinical Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cancer Care Ontario; Grand River Hospital; University of Waterloo","funders":"","keywords":"Standard deviation; Imaging phantom; Context (archaeology); Margin (machine learning); Radiation treatment planning; Breathing; Nuclear medicine; External beam radiation; Probability density function; Physics; Radiation therapy; Statistics; Materials science; Mathematics; Optics; Computer science; Medicine; Radiology","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":[0.001183659,0.0001654049,0.0006140316,0.00005017456,0.00005078693,0.00001155744,0.0003672503,0.0000987296,0.00004363317],"category_scores_gemma":[0.0001160681,0.0001191511,0.0003009664,0.0002612949,0.0000840107,0.0001159917,0.00005020887,0.0004295695,8.089344e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008527963,"about_ca_system_score_gemma":0.0001853697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000681442,"about_ca_topic_score_gemma":1.533625e-7,"domain_scores_codex":[0.9977301,0.0000890186,0.001113972,0.0001835191,0.0006786567,0.000204736],"domain_scores_gemma":[0.9978402,0.0003301068,0.001002234,0.0001997425,0.0003166017,0.0003111774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01693553,0.007492702,0.2038792,0.0002749198,0.001840907,0.00001475518,0.003105974,0.09130181,0.122666,0.03903089,0.008616921,0.5048404],"study_design_scores_gemma":[0.01759783,0.002831826,0.06393388,0.0005823247,0.0001268484,0.00001893335,0.0001103847,0.01013183,0.6739345,0.2203439,0.009603487,0.0007842804],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4398787,0.00002952754,0.5590813,0.0002351783,0.0002390278,0.0004438419,0.00001327992,0.000007850931,0.00007130919],"genre_scores_gemma":[0.9717131,0.00003008947,0.02610639,0.0003172458,0.001761267,0.00002448069,0.000003761147,0.00003062054,0.00001305317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5512685,"threshold_uncertainty_score":0.4858841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02026058404174718,"score_gpt":0.3392083073503515,"score_spread":0.3189477233086043,"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."}}