{"id":"W2053686058","doi":"10.1118/1.3246352","title":"Implementation and characterization of a 320‐slice volumetric CT scanner for simulation in radiation oncology","year":2009,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Scanner; Collimated light; Nuclear medicine; Image quality; Medical physics; Medical imaging; Image resolution; Cone beam computed tomography; Dosimetry; Radiation treatment planning; Medicine; Biomedical engineering; Materials science; Radiation therapy; Computer science; Computed tomography; Optics; Physics; Radiology; Artificial intelligence","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":[0.0001312958,0.00006370422,0.0001397403,0.00006066501,0.00002297632,0.00000482607,0.00004003356,0.0000245873,0.00004281789],"category_scores_gemma":[0.00001149023,0.00006434618,0.0000242102,0.0002190412,0.00002078983,0.0001613062,0.000004991158,0.00005762542,1.572109e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000450185,"about_ca_system_score_gemma":0.0000432427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003434072,"about_ca_topic_score_gemma":0.000001846764,"domain_scores_codex":[0.9994349,0.00002546865,0.0002068874,0.0001132973,0.0001214992,0.00009791397],"domain_scores_gemma":[0.9996438,0.00008695191,0.0001397923,0.00005759664,0.00003752551,0.00003436027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001666203,0.000104828,0.02010934,0.000006755909,0.000006848591,1.132464e-7,0.0001726898,0.00009429513,0.005396039,0.002173832,0.00001599961,0.9719026],"study_design_scores_gemma":[0.01033332,0.002038118,0.4076612,0.00011197,0.00008925577,0.00000116807,0.0001993096,0.3184555,0.1695135,0.07204191,0.01878153,0.0007732147],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3623785,0.00001090376,0.6370649,0.0001533766,0.00002445669,0.0002826638,0.00001256138,0.00001229748,0.00006031394],"genre_scores_gemma":[0.9981579,0.00001388246,0.001248178,0.0001265694,0.0002178972,0.00002837152,0.0001927865,0.000006978373,0.000007398793],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9711294,"threshold_uncertainty_score":0.2623961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0113266413813535,"score_gpt":0.3576821617828687,"score_spread":0.3463555204015152,"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."}}