{"id":"W2177515058","doi":"10.1016/j.jmir.2015.09.012","title":"Cone Beam Computed Tomography: The Challenges and Strategies in Its Application for Dose Accumulation","year":2015,"lang":"en","type":"review","venue":"Journal of medical imaging and radiation sciences","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Cone beam computed tomography; Cone beam ct; Computation; Reliability (semiconductor); Computed tomography; Nuclear medicine; Computer science; Radiation dose; Image-guided radiation therapy; Volume (thermodynamics); Image quality; Medicine; Medical physics; Radiology; Image (mathematics); Artificial intelligence; Algorithm; Physics","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":[0.002006837,0.0001126914,0.0004098468,0.0002036755,0.00009318963,0.00008563249,0.0002126301,0.00005089838,0.000002297124],"category_scores_gemma":[0.00003679194,0.00006342865,0.00006336933,0.0001854497,0.0002218337,0.0003581792,0.00001762061,0.0002063632,4.892429e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001679191,"about_ca_system_score_gemma":0.0002942569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006379212,"about_ca_topic_score_gemma":7.675854e-7,"domain_scores_codex":[0.9988819,0.00008827567,0.0004066848,0.0001406812,0.00038009,0.0001024143],"domain_scores_gemma":[0.9987879,0.0004220596,0.0005694747,0.00005164709,0.00009229044,0.00007657701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001437384,0.00001379009,0.00005300875,0.0001462863,0.00001533787,2.104903e-7,0.0001928537,0.0000166687,6.974086e-7,0.004379056,0.00005983641,0.9951208],"study_design_scores_gemma":[0.0006954459,0.00009362347,0.0003760793,0.002328283,0.0001075227,0.00004056716,0.001544434,0.01729527,0.000002848969,0.01307742,0.9642279,0.0002106811],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005315103,0.9580344,0.04026606,0.001201446,0.00009753029,0.0002981773,0.000003680026,0.000006798551,0.00003876822],"genre_scores_gemma":[0.003741867,0.9945346,0.001204097,0.00002509323,0.0004602254,0.00002324112,0.000003858005,0.000005904004,0.000001121958],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9949101,"threshold_uncertainty_score":0.2586545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07316500017215506,"score_gpt":0.4280647206599652,"score_spread":0.3548997204878102,"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."}}