{"id":"W2173925012","doi":"10.1109/rtc.2007.4382813","title":"Timing improvement by low-pass filtering and linear interpolation for the LabPET&lt;sup&gt;TM&lt;/sup&gt; scanner","year":2007,"lang":"en","type":"article","venue":"","topic":"Radiation Detection and Scintillator Technologies","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Interpolation (computer graphics); Scanner; Timestamp; Lyso-; Algorithm; Energy (signal processing); Computer science; Image resolution; Filter (signal processing); Coincidence; Resolution (logic); Physics; Artificial intelligence; Computer vision; Real-time computing; Optics; Detector","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":[0.0002769774,0.0001498368,0.0001289475,0.00008011178,0.0002524148,0.0001042339,0.0001285577,0.00006116417,0.0002631803],"category_scores_gemma":[0.00001763162,0.0001088453,0.00007365927,0.0001231499,0.00004900228,0.0001503996,0.0000679413,0.0001069472,0.00001300996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003139843,"about_ca_system_score_gemma":0.00001061755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004748045,"about_ca_topic_score_gemma":0.00001757266,"domain_scores_codex":[0.9991096,0.000007851514,0.0002717032,0.0002359845,0.0001186535,0.00025619],"domain_scores_gemma":[0.999464,0.000115386,0.000102097,0.0002056836,0.00006159277,0.00005124529],"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":[0.0001371529,0.0001489838,0.006414271,0.00006374483,0.000368387,8.216811e-7,0.001264839,0.003989292,0.220846,0.01429246,0.03096325,0.7215108],"study_design_scores_gemma":[0.001266783,0.0002180791,0.001905235,0.00003474085,0.00004441453,0.00000133568,0.002887289,0.6673687,0.1230204,0.0005554868,0.2022174,0.0004801256],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7455103,0.0000784344,0.2498847,0.001057619,0.0002632297,0.0005416307,0.00003642581,0.0001987135,0.002428911],"genre_scores_gemma":[0.9953375,0.000007097119,0.001906063,0.0001359127,0.0002157481,0.0000392181,0.000007766711,0.00001774575,0.002332954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7210307,"threshold_uncertainty_score":0.4438584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009836914661378177,"score_gpt":0.2435410134119319,"score_spread":0.2337040987505537,"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."}}