{"id":"W4230215693","doi":"10.1109/nssmic.1998.774352","title":"A pixelated 3D Auger camera with light-loss compensation","year":2002,"lang":"en","type":"article","venue":"1998 IEEE Nuclear Science Symposium Conference Record. 1998 IEEE Nuclear Science Symposium and Medical Imaging Conference (Cat. No.98CH36255)","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TRIUMF","funders":"TRIUMF","keywords":"Monte Carlo method; Compensation (psychology); Optics; Image resolution; Auger; Resolution (logic); Materials science; Physics; Computer science; Artificial intelligence; Atomic physics","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts"],"category_scores_codex":[0.001937513,0.001443582,0.001341683,0.001419476,0.002273638,0.00259415,0.004692048,0.0005190647,0.0005511943],"category_scores_gemma":[0.0005440539,0.001269341,0.0001939375,0.003725538,0.01518928,0.005476556,0.0007848868,0.001759256,0.001957296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008498449,"about_ca_system_score_gemma":0.0009316548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002495845,"about_ca_topic_score_gemma":0.00004806025,"domain_scores_codex":[0.988022,0.0001452641,0.001413702,0.003008707,0.003936004,0.003474324],"domain_scores_gemma":[0.9937731,0.0002736751,0.0004690191,0.00203071,0.001178075,0.00227541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006994916,0.0002943233,0.0008610291,0.0001864134,0.00005572361,0.0002119785,0.003378623,0.0005405082,0.9547085,0.002720099,0.001082079,0.03589076],"study_design_scores_gemma":[0.001230107,0.0003989308,0.0003155634,0.0008651619,0.0000995498,0.0005517608,0.0009823946,0.9827204,0.003677815,0.0002604774,0.007065358,0.001832496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9570879,0.00002520908,0.005376854,0.007533667,0.003977451,0.001102342,0.0000310977,0.003764428,0.02110109],"genre_scores_gemma":[0.9324017,0.002362939,0.06324062,0.001077788,0.0003088942,0.00005688954,0.000004798439,0.0002286529,0.0003176882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9821799,"threshold_uncertainty_score":0.9998314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009991695844528893,"score_gpt":0.2205837544621343,"score_spread":0.2105920586176054,"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."}}