{"id":"W2545106557","doi":"10.1109/nssmic.2012.6551616","title":"Polyenergetic CT sinogram generator","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Software; Generator (circuit theory); Weighting; Attenuation; Energy (signal processing); Iterative reconstruction; Noise (video); Artificial intelligence; Computer vision; Electronic engineering; Computer engineering; Image (mathematics); Optics; Acoustics; Mathematics; Physics; 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":[0.0005097885,0.0005860642,0.0003628274,0.0007089495,0.0001440557,0.0006735329,0.001081505,0.0005967601,0.0256189],"category_scores_gemma":[0.001982286,0.0003018818,0.000331933,0.000583417,0.000215185,0.0003794592,0.0005329092,0.000517451,0.003909789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000249613,"about_ca_system_score_gemma":0.0004633339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002972962,"about_ca_topic_score_gemma":0.0003092304,"domain_scores_codex":[0.9998296,0.00003195047,0.00002022397,0.00004166884,0.00006596461,0.0000105174],"domain_scores_gemma":[0.9993431,0.0002823599,0.00004595563,0.0001156759,0.0001759264,0.00003690368],"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":[0.002299476,0.0001953049,0.00470939,0.001413192,0.0001367227,0.002785521,0.0003578506,0.08882639,0.1281354,0.04061328,0.04186405,0.6886634],"study_design_scores_gemma":[0.0003149786,0.0004222484,0.002819164,0.0001183425,0.00006757423,0.003830041,0.00006469401,0.7606283,0.1365842,0.008086216,0.08696774,0.00009648843],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006498721,0.0000725962,0.9821911,0.0000755123,0.00009770386,0.0002664838,0.0007029823,0.007593031,0.002501787],"genre_scores_gemma":[0.1525504,0.0002816232,0.830264,0.0002700779,0.00007022268,0.0009941881,0.002603242,0.003030528,0.00993573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0256189,"threshold_uncertainty_score":0.08570367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006817336783314162,"score_gpt":0.2052793764450596,"score_spread":0.1984620396617454,"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."}}