{"id":"W2014929720","doi":"10.1016/j.compmedimag.2006.12.003","title":"Assessment of glucose metabolism from the projections using the wavelet technique in small animal pet imaging","year":2007,"lang":"en","type":"article","venue":"Computerized Medical Imaging and Graphics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Wavelet; Iterative reconstruction; Parametric statistics; Projection (relational algebra); Image resolution; Filter (signal processing); Positron emission tomography; Artificial intelligence; Nuclear medicine; Mathematics; Computer science; Pattern recognition (psychology); Image quality; Computer vision; Algorithm; Image (mathematics); Medicine; Statistics","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":[0.002353641,0.0002026944,0.0003961731,0.0001775945,0.0002318819,0.00004416584,0.0003246389,0.0000644686,0.00001837707],"category_scores_gemma":[0.0002533335,0.0001205949,0.0001199052,0.0006694529,0.0008801068,0.00005523647,0.0002573374,0.0009820568,1.774867e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003219286,"about_ca_system_score_gemma":0.0002416626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001038996,"about_ca_topic_score_gemma":0.00003347355,"domain_scores_codex":[0.9980904,0.0001368057,0.0005970394,0.0003569987,0.0004603529,0.0003583275],"domain_scores_gemma":[0.998325,0.0006605522,0.000162162,0.0004876596,0.0001321146,0.0002325122],"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":[0.000346866,0.002263806,0.3219141,0.0005320602,0.0004564443,0.00148998,0.00227471,0.000004253252,0.3729858,0.08489465,0.005727551,0.2071097],"study_design_scores_gemma":[0.002903939,0.00005615627,0.250036,0.001402206,0.0003575324,0.001623952,0.0005331878,0.7184449,0.004304809,0.006046206,0.01387614,0.0004149436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3720528,0.0007915197,0.6054154,0.02052326,0.0001256435,0.0008170072,0.00001222508,0.0001314421,0.0001306428],"genre_scores_gemma":[0.8494871,0.0003852864,0.1462767,0.003476958,0.00026281,0.00005854768,0.00002544259,0.00002395245,0.000003215376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7184407,"threshold_uncertainty_score":0.4917716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02666874613227405,"score_gpt":0.3456867968146057,"score_spread":0.3190180506823316,"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."}}