{"id":"W2000406815","doi":"10.1016/j.nima.2008.10.024","title":"A handy time alignment probe for timing calibration of PET scanners","year":2008,"lang":"en","type":"article","venue":"Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment","topic":"Radiation Detection and Scintillator Technologies","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Detector; Scintillation; Coincidence; Timestamp; Calibration; Dead time; Lyso-; Scanner; Physics; Optics; Coincidence detection in neurobiology; Liquid scintillation counting; Coincidence counting; Scintillator; Tracking (education); Photomultiplier; Data acquisition; Scintillation counter; Computer science; Real-time computing; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001757295,0.0007137334,0.000787515,0.001021735,0.001020714,0.001765765,0.00201675,0.001683186,0.01540287],"category_scores_gemma":[0.00829851,0.0006959971,0.0002113337,0.001151312,0.0007276616,0.001628362,0.001977838,0.001214059,0.002607696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001376515,"about_ca_system_score_gemma":0.001695706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001166063,"about_ca_topic_score_gemma":0.002064027,"domain_scores_codex":[0.9981686,0.000301451,0.0001041223,0.0004609077,0.0008107173,0.0001541847],"domain_scores_gemma":[0.9960522,0.001331036,0.0005742093,0.000925888,0.0008554853,0.0002611734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002544935,0.0001234805,0.003524157,0.0003179106,0.00005185731,0.0004351788,0.0005731725,0.002738765,0.6459197,0.01141046,0.00589594,0.3264646],"study_design_scores_gemma":[0.0002024634,0.001187118,0.008476266,0.0001500133,0.0001264346,0.002602103,0.0002160509,0.0845458,0.8214465,0.003358874,0.07749707,0.0001912661],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08016331,0.001117068,0.8945213,0.0007986181,0.0006406339,0.0004132137,0.0004954563,0.01131785,0.0105326],"genre_scores_gemma":[0.4320131,0.00034157,0.5525781,0.0009500211,0.0001713402,0.0003681181,0.0003729615,0.001536461,0.01166833],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01540287,"threshold_uncertainty_score":0.0515278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06324228526824685,"score_gpt":0.3655131229137376,"score_spread":0.3022708376454907,"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."}}