{"id":"W3182216805","doi":"10.1002/acm2.13336","title":"Technical Note: Volumetric computed tomography for radiotherapy simulation and treatment planning","year":2021,"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":"Lawson Health Research Institute; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Lawson Health Research Institute","keywords":"Scanner; Image quality; Nuclear medicine; Contouring; Computed tomography; Medicine; Linearity; Image noise; Hounsfield scale; Image-guided radiation therapy; Mathematics; Computer science; Radiology; Physics; Artificial intelligence; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004953279,0.0001954512,0.000697375,0.00007078912,0.00008354898,0.00003167719,0.0001632053,0.0001687671,0.00005035206],"category_scores_gemma":[0.00008095631,0.0001563026,0.0003912474,0.0003713406,0.0001718713,0.00008311152,0.00002782652,0.0004595564,2.551309e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005632919,"about_ca_system_score_gemma":0.0002019521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001024618,"about_ca_topic_score_gemma":1.137162e-7,"domain_scores_codex":[0.9981281,0.00005675395,0.0009313108,0.0002586031,0.000403929,0.0002212795],"domain_scores_gemma":[0.9965652,0.002244669,0.0005168443,0.0001863866,0.0001868896,0.0002999764],"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":[0.0003684572,0.001055552,0.008691143,0.00001245846,0.0002611417,0.00001266784,0.00006713068,0.002827423,0.0007371815,0.005003657,0.0004256377,0.9805375],"study_design_scores_gemma":[0.044632,0.009596878,0.01958984,0.0008266549,0.001096454,0.00006972796,0.0002024581,0.4805571,0.01724599,0.2337115,0.190193,0.00227831],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01120152,0.0004284477,0.9874359,0.0002410333,0.0002014232,0.0002463104,0.000008936197,0.00003533707,0.0002010536],"genre_scores_gemma":[0.7049576,0.000126894,0.290931,0.0004629013,0.003438901,0.00001811332,0.00001562061,0.00003964031,0.000009287192],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9782593,"threshold_uncertainty_score":0.6373835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03475928979274929,"score_gpt":0.3964575903234279,"score_spread":0.3616983005306786,"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."}}