{"id":"W1568763973","doi":"10.1118/1.4923999","title":"SU‐E‐I‐02: Characterizing Low‐Contrast Resolution for Non‐Circular CBCT Trajectories","year":2015,"lang":"en","type":"article","venue":"Medical Physics","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Imaging phantom; Quality assurance; Image quality; Image resolution; Calibration; Field of view; Computer science; Resolution (logic); Contrast (vision); Optics; Artificial intelligence; Physics; Image (mathematics); Engineering","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":[0.0009939844,0.0003230156,0.0001554401,0.0006765188,0.0001566514,0.000682646,0.0005985164,0.0005292252,0.001286784],"category_scores_gemma":[0.002400699,0.0003180523,0.000138265,0.0004787999,0.0003679107,0.0005592236,0.0002684224,0.0003611596,0.000303232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004792171,"about_ca_system_score_gemma":0.0004330868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001986769,"about_ca_topic_score_gemma":0.002472888,"domain_scores_codex":[0.9997506,0.00004697153,0.00001919284,0.0000463232,0.0001085642,0.00002835369],"domain_scores_gemma":[0.9990521,0.0004189959,0.0001886748,0.0001117333,0.0001606522,0.00006786024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001674563,0.000252383,0.01671621,0.0003201881,0.000053089,0.0001701338,0.0001789338,0.01080789,0.9105011,0.001080067,0.0007483658,0.05749702],"study_design_scores_gemma":[0.00004119933,0.0009595475,0.02846442,0.00002750709,0.00005338733,0.0008401341,0.00006292052,0.1030123,0.8640468,0.0002497652,0.00219268,0.00004931149],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.826248,0.002283526,0.1650083,0.0001347087,0.0000192945,0.000149732,0.0003796552,0.001715195,0.004061644],"genre_scores_gemma":[0.8901134,0.0006022262,0.1055682,0.0001096072,0.00000624771,0.0001307049,0.0008747415,0.0002985047,0.002296269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001986769,"threshold_uncertainty_score":0.005256712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02887474439557102,"score_gpt":0.2885999619531381,"score_spread":0.2597252175575671,"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."}}