{"id":"W2167336982","doi":"10.1088/0031-9155/50/19/015","title":"Correction of artefacts in optical projection tomography","year":2005,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Projection (relational algebra); Optics; Tomography; Resolution (logic); Detector; Pixel; Computer vision; Truncation (statistics); Image quality; Computer science; Artificial intelligence; Image resolution; Physics; Position (finance); Field of view; Angular resolution (graph drawing); SIGNAL (programming language); Image (mathematics); Mathematics; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009239923,0.00005121442,0.0001287439,0.00008490919,0.000005496758,6.824502e-7,0.00001980895,0.00003591184,0.000003959542],"category_scores_gemma":[0.00002561325,0.00004169071,0.000008530254,0.0001691809,0.00007097881,0.00003216532,0.000004289155,0.0001230243,4.390015e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001491056,"about_ca_system_score_gemma":0.000004671457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005104146,"about_ca_topic_score_gemma":0.00002847446,"domain_scores_codex":[0.9996786,0.000009163624,0.0001211748,0.00006931762,0.00002170606,0.0001000225],"domain_scores_gemma":[0.9998585,0.0000711537,0.00001185755,0.00003668348,0.000008181832,0.0000136221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002511941,0.0001172607,0.0478866,0.0001093936,0.00002517014,0.00000236304,0.002183441,0.01206486,0.1989223,0.002383481,0.000838452,0.7354415],"study_design_scores_gemma":[0.00239527,0.0003726514,0.06888979,0.000398864,0.00003350907,0.00002821338,0.001370371,0.8827187,0.03570476,0.004601383,0.003179345,0.0003071743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9761171,0.0003076338,0.0112479,0.0001222673,0.0004644048,0.00008626963,7.948226e-7,0.00003053769,0.01162305],"genre_scores_gemma":[0.9994254,0.0001864527,0.0001678134,0.00003947386,0.0001653269,0.000004716475,0.000004000704,0.000002958025,0.000003854615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8706538,"threshold_uncertainty_score":0.1700098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0621493251277843,"score_gpt":0.3170645876113997,"score_spread":0.2549152624836154,"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."}}