{"id":"W1024585430","doi":"10.3233/xst-2010-0277","title":"A novel hybrid reconstruction algorithm for first generation incoherent scatter CT (ISCT) of large objects with potential medical imaging applications","year":2011,"lang":"en","type":"article","venue":"Journal of X-Ray Science and Technology","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; CancerCare Manitoba","funders":"CancerCare Manitoba Foundation; Manitoba Health Research Council","keywords":"Algorithm; Iterative reconstruction; Detector; Monte Carlo method; Reconstruction algorithm; Computer science; Projection (relational algebra); Photon; Medical imaging; Computer vision; Artificial intelligence; Physics; Mathematics; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007129458,0.00007871723,0.0002059441,0.0004299495,0.0001706564,0.00001148844,0.0002019962,0.00003953985,0.00002737834],"category_scores_gemma":[0.000120893,0.00005487302,0.00003416988,0.0004736497,0.0009159149,0.0001578776,0.0000510865,0.0002150847,5.125838e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003982981,"about_ca_system_score_gemma":0.0003798537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008803986,"about_ca_topic_score_gemma":0.00000479472,"domain_scores_codex":[0.9988845,0.000004354505,0.0003541977,0.0001836575,0.0003939892,0.000179298],"domain_scores_gemma":[0.9986857,0.00001571675,0.0003001206,0.0001752746,0.0006902394,0.0001329995],"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":[0.00003609037,0.0008199509,0.005526578,0.00007098531,0.00005729503,0.00003625088,0.000117777,7.912918e-7,0.1998367,0.003116209,0.001304883,0.7890765],"study_design_scores_gemma":[0.01132607,0.003130083,0.0069308,0.001432305,0.0008418565,0.05638792,0.002073325,0.2612461,0.6274944,0.01018432,0.01821263,0.0007401947],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1686031,0.00008980703,0.8233775,0.007371608,0.00006792971,0.0003877499,0.000006428937,0.00003073547,0.00006515939],"genre_scores_gemma":[0.7758544,0.0000647967,0.2237233,0.0001825888,0.0001069925,0.00005384726,0.000001787949,0.000005653555,0.000006659989],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7883363,"threshold_uncertainty_score":0.3374727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01460841800728284,"score_gpt":0.2761339861205186,"score_spread":0.2615255681132357,"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."}}