{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002047437,0.0003989091,0.0002111591,0.0003242791,0.0001437799,0.000480816,0.001088102,0.0004408361,0.002287075],"category_scores_gemma":[0.002911506,0.0002768409,0.0002700955,0.0002696935,0.0002174088,0.0003109515,0.0003826642,0.0002947559,0.0006016057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004198628,"about_ca_system_score_gemma":0.001242981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009528638,"about_ca_topic_score_gemma":0.000733597,"domain_scores_codex":[0.9995561,0.0001360554,0.00004566308,0.0000542157,0.0001786725,0.00002931168],"domain_scores_gemma":[0.9985318,0.0004489514,0.0001250491,0.0002167296,0.0006068423,0.00007051955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001039838,0.000274685,0.03154261,0.0006151943,0.00007879658,0.0008261761,0.0005063142,0.0518812,0.7487625,0.003019869,0.002927308,0.1585254],"study_design_scores_gemma":[0.0002557656,0.002375439,0.03465869,0.0001519982,0.0001589745,0.00419136,0.000144557,0.2832785,0.6312292,0.0008017723,0.04262584,0.0001278375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2265871,0.0004366093,0.7655828,0.0002394291,0.00006865035,0.0008741652,0.0007904933,0.002740043,0.002680607],"genre_scores_gemma":[0.5624917,0.0002144047,0.4339689,0.00009025956,0.00002266827,0.000582181,0.001145377,0.0003503074,0.001134132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002287075,"threshold_uncertainty_score":0.01082802,"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."}}