{"id":"W2170622221","doi":"10.1109/tns.2009.2015946","title":"Signal Deconvolution Concept Combined With Cubic Spline Interpolation to Improve Timing With Phoswich PET Detectors","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Nuclear Science","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Deconvolution; Lyso-; Detector; Physics; Computer science; Spline interpolation; Interpolation (computer graphics); Signal processing; Electronic engineering; Algorithm; Computational science; Scintillator; Optics; Digital signal processing; Computer hardware; Computer vision; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000173581,0.0001399421,0.0001610261,0.0002173779,0.0003297533,0.00005267096,0.0001737297,0.00003069896,0.0001739177],"category_scores_gemma":[0.000007814748,0.0001037925,0.00003515614,0.0008464154,0.0003358693,0.0002083702,0.000001609737,0.0002656727,0.00003843976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001325902,"about_ca_system_score_gemma":0.0001194778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003481988,"about_ca_topic_score_gemma":0.000010359,"domain_scores_codex":[0.9987298,0.00001079873,0.0001766917,0.0003953744,0.0004176769,0.0002696841],"domain_scores_gemma":[0.9991431,0.00002601713,0.00005782041,0.0003161115,0.0001591405,0.0002978533],"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":[0.001610728,0.0009316196,0.00004743197,0.00002453688,0.00003099157,0.00002953139,0.001043746,0.003034136,0.8955086,0.0004458208,0.0006372367,0.09665558],"study_design_scores_gemma":[0.002891291,0.01380269,0.003155936,0.0006116011,0.0002039188,0.0003386645,0.000396588,0.6932847,0.2836721,0.00007313977,0.0009776856,0.0005917036],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5411704,0.000001343928,0.4547638,0.003124065,0.00004527259,0.0004818999,0.000004284475,0.0002238638,0.0001850853],"genre_scores_gemma":[0.9328017,0.000002290443,0.06584473,0.001161725,0.00002394963,0.00002091987,6.933802e-7,0.00001557705,0.0001283964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6902505,"threshold_uncertainty_score":0.4232536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01206207797941484,"score_gpt":0.2769068469650631,"score_spread":0.2648447689856483,"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."}}