{"id":"W2495294076","doi":"","title":"폐암 SBRT에서 호흡동조 VMAT의 정확성 분석을 위한 새로운 4D 팬텀 모델 개발","year":2014,"lang":"ko","type":"article","venue":"의학물리 = Korean journal of medical physics","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Imaging phantom; Nuclear medicine; Medicine; Radiation treatment planning; Homogeneous; Radiosurgery; Radiation therapy; Lung cancer; Mathematics; Radiology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001045049,0.0006941285,0.0004997284,0.001461614,0.0006269834,0.003922863,0.000855979,0.0009125094,0.01077835],"category_scores_gemma":[0.001605934,0.0006419754,0.0009640725,0.001204581,0.001174487,0.002339383,0.001140727,0.001122597,0.003417966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001594024,"about_ca_system_score_gemma":0.002257643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00653371,"about_ca_topic_score_gemma":0.007344975,"domain_scores_codex":[0.9992022,0.0001633117,0.00005004639,0.0001334433,0.0003831558,0.00006786481],"domain_scores_gemma":[0.9993188,0.0001333379,0.0000668276,0.00009204047,0.00032064,0.00006832396],"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":[0.0003735998,0.0001185317,0.01171764,0.001301044,0.0002017791,0.0003584585,0.0006871106,0.05464794,0.02298818,0.105361,0.0481807,0.754064],"study_design_scores_gemma":[0.0001366811,0.0002513423,0.01095683,0.000681727,0.0003853989,0.002294528,0.0009319122,0.1939194,0.03377881,0.08249303,0.673824,0.0003463119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05214265,0.02812962,0.7078807,0.008380087,0.001353965,0.0003012893,0.003211068,0.004721648,0.193879],"genre_scores_gemma":[0.4269126,0.01846104,0.4983142,0.002399375,0.0006684623,0.0004411231,0.003319896,0.002036302,0.04744696],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01077835,"threshold_uncertainty_score":0.03605711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021573821469236,"score_gpt":0.2473750354943044,"score_spread":0.237159297279612,"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."}}