{"id":"W4220989370","doi":"10.1117/12.2608906","title":"Cupping correction for partial rotation dental conebeam CT","year":2022,"lang":"en","type":"article","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Imaging phantom; Physics; Offset (computer science); Optics; Nuclear medicine; Image quality; Cone beam computed tomography; Medical imaging; Attenuation; Field of view; Image-guided radiation therapy; Field size; Computed tomography; Computer science; Medicine; Computer vision; Artificial intelligence; Image (mathematics)","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":[0.002218922,0.001388141,0.0006700145,0.001737903,0.0008144004,0.001758862,0.001771922,0.001038918,0.006079861],"category_scores_gemma":[0.012564,0.0007781023,0.001435516,0.001910144,0.0005912985,0.00090842,0.001287261,0.001163019,0.001608401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118263,"about_ca_system_score_gemma":0.002253098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01013352,"about_ca_topic_score_gemma":0.008394334,"domain_scores_codex":[0.9983749,0.0003028117,0.0001499333,0.0002589503,0.0007918334,0.0001215413],"domain_scores_gemma":[0.9956669,0.001528558,0.0005204239,0.0006909662,0.001485081,0.0001080631],"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":[0.001200267,0.0001205801,0.01381703,0.002199266,0.0003612651,0.00194304,0.001234264,0.2083539,0.1103387,0.01941159,0.0387278,0.6022924],"study_design_scores_gemma":[0.00007770833,0.0002374274,0.01519025,0.0002436989,0.0003944229,0.003697057,0.0002251082,0.7692118,0.1185868,0.004727943,0.08703347,0.0003742733],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0276344,0.001342923,0.9606202,0.0002460693,0.0004134766,0.0001803362,0.0004653163,0.006181555,0.002915832],"genre_scores_gemma":[0.3327717,0.001358453,0.6543738,0.0004163073,0.00008362633,0.0002090281,0.001681204,0.00418677,0.004919075],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01013352,"threshold_uncertainty_score":0.02033913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02827405801069123,"score_gpt":0.3422796871638933,"score_spread":0.3140056291532021,"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."}}