{"id":"W2028265794","doi":"10.1118/1.1997806","title":"SU‐FF‐T‐135: Complex IMRT Plan Verification Using a Commercial MU Calculation Package","year":2005,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pinnacle; Dosimetry; Imaging phantom; Nuclear medicine; Head and neck; Radiation treatment planning; Population; Medical physics; Medicine; Computer science; Radiation therapy; Radiology; Surgery","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":[0.001403561,0.00086816,0.0004870461,0.0008076567,0.000371401,0.0008272467,0.001490041,0.0003552008,0.04225855],"category_scores_gemma":[0.003406918,0.0006781087,0.0006009512,0.0005824394,0.0002540316,0.0006126454,0.000697038,0.0004408915,0.00572058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008349113,"about_ca_system_score_gemma":0.00116505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002775687,"about_ca_topic_score_gemma":0.003314585,"domain_scores_codex":[0.9994653,0.00008263539,0.00006631151,0.0001017014,0.000251155,0.00003283829],"domain_scores_gemma":[0.9986702,0.0004146858,0.0001754384,0.0003400957,0.0003675188,0.0000320287],"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":[0.002053568,0.00036686,0.01296122,0.001257922,0.0003577446,0.0003545993,0.000533429,0.1016882,0.1297146,0.01157491,0.07911162,0.6600254],"study_design_scores_gemma":[0.0004671406,0.0006237797,0.01801509,0.00008434553,0.0001648213,0.001561545,0.00007313454,0.6564066,0.2368575,0.002702334,0.08286089,0.0001829444],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05345056,0.0002601135,0.8213995,0.0001041428,0.00005305993,0.0005118125,0.004530712,0.1043052,0.01538486],"genre_scores_gemma":[0.358637,0.0001133788,0.5950599,0.0001359955,0.00002276595,0.0007382259,0.009168775,0.02622166,0.009902376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04225855,"threshold_uncertainty_score":0.141369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04032042121263558,"score_gpt":0.3315936902542601,"score_spread":0.2912732690416245,"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."}}