{"id":"W2081513122","doi":"10.1088/0031-9155/56/10/003","title":"Single scan parameterization of space-variant point spread functions in image space via a printed array: the impact for two PET/CT scanners","year":2011,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Engineering and Physical Sciences Research Council","keywords":"Imaging phantom; Image resolution; Image quality; Iterative reconstruction; Field of view; Computer vision; Point source; Artificial intelligence; Projection (relational algebra); Physics; Computer science; Point spread function; Optics; Algorithm; 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":[0.001416673,0.000591654,0.0004973562,0.0004175243,0.000171341,0.001557084,0.0008165886,0.00135093,0.001569736],"category_scores_gemma":[0.006523068,0.0005198757,0.0004763735,0.0006028346,0.0003472043,0.001101228,0.0007041586,0.0007992423,0.0006192237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000537695,"about_ca_system_score_gemma":0.0004095536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006313879,"about_ca_topic_score_gemma":0.0006557616,"domain_scores_codex":[0.9989845,0.0003398719,0.00005227576,0.000168533,0.0004066933,0.00004810287],"domain_scores_gemma":[0.9968064,0.001584389,0.0003356165,0.0007760577,0.0003856992,0.0001118843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001717793,0.0002737481,0.007902957,0.0003879741,0.0002349977,0.0009132851,0.000314072,0.2840744,0.5007047,0.003474593,0.001063667,0.1989379],"study_design_scores_gemma":[0.00003854357,0.0005226277,0.008600312,0.00002606062,0.0001053523,0.00215125,0.00008113551,0.6592454,0.324187,0.001234744,0.003682457,0.0001252568],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.164481,0.0004108276,0.8305015,0.0002848027,0.00005324818,0.00006853032,0.0001085695,0.002613957,0.001477599],"genre_scores_gemma":[0.6502285,0.0002517703,0.3466205,0.0001409537,0.00002448544,0.00008846875,0.0001960958,0.0005260028,0.001923139],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001569736,"threshold_uncertainty_score":0.007492125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1437319762940014,"score_gpt":0.3990109571122584,"score_spread":0.2552789808182571,"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."}}