{"id":"W1965828060","doi":"10.1118/1.1799291","title":"The impact of tumor motion upon CT image integrity and target delineation","year":2004,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Volume rendering; Imaging phantom; Computer vision; Computer science; Conformal map; Artificial intelligence; Image quality; Rendering (computer graphics); Iterative reconstruction; Radiation therapy; Partial volume; Motion (physics); Nuclear medicine; Mathematics; Image (mathematics); Radiology; Medicine; Geometry","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":[0.0001649386,0.00009061371,0.0001228198,0.000008713069,0.00007153962,0.00001273379,0.00009485606,0.00001433948,0.0000482014],"category_scores_gemma":[0.00003030882,0.00005555824,0.000074057,0.00007775184,0.0001251627,0.0001186176,0.00002170211,0.0002488871,0.000001007638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004284613,"about_ca_system_score_gemma":0.00007895035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003747758,"about_ca_topic_score_gemma":0.000001209342,"domain_scores_codex":[0.9994144,0.00002441439,0.0001513535,0.0001034633,0.0001857434,0.0001206315],"domain_scores_gemma":[0.9996092,0.00005429532,0.00008626626,0.0001313241,0.00005499934,0.00006390135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008917946,0.000874605,0.05823368,0.00003351148,0.0002234029,0.000006338433,0.0004938216,0.0008455918,0.01467357,0.0592085,0.0008750429,0.8644428],"study_design_scores_gemma":[0.001652548,0.0003448112,0.01040037,0.0001093374,0.00002442927,0.000005542077,0.00006473463,0.01380032,0.2692122,0.7034399,0.0006161103,0.0003297282],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2359615,0.00004217857,0.7635265,0.0001635638,0.0000225917,0.00009228761,0.00001130825,0.00002423527,0.0001558287],"genre_scores_gemma":[0.9936816,0.00001613536,0.005964915,0.00001875539,0.0002717842,0.000009556037,0.00002006196,0.00001087308,0.000006330195],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.864113,"threshold_uncertainty_score":0.2265599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008244509048619763,"score_gpt":0.3071908488905339,"score_spread":0.2989463398419142,"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."}}