{"id":"W4305072495","doi":"10.1016/j.nima.2022.167567","title":"A proposed energy calibration procedure taking into account high per pixel energies using a silicon TPX3 detector","year":2022,"lang":"en","type":"article","venue":"Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Van de Graaff generator; Calibration; Detector; Range (aeronautics); Physics; Energy (signal processing); Pixel; Proton; Ion; Nuclear physics; Atomic physics; Saturation (graph theory); Computational physics; Optics; Materials science; Beam (structure); Mathematics","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":[0.0007413042,0.000851898,0.0006635219,0.0007686913,0.000696776,0.001291387,0.001803447,0.001514106,0.007904988],"category_scores_gemma":[0.0007695522,0.0005225024,0.0007802938,0.000985681,0.0003179832,0.0009715154,0.0008784534,0.0008500277,0.004597249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005073804,"about_ca_system_score_gemma":0.001274899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001160012,"about_ca_topic_score_gemma":0.002235373,"domain_scores_codex":[0.999268,0.00008144562,0.00003085536,0.0002379576,0.0003356156,0.00004619173],"domain_scores_gemma":[0.9996295,0.00004660569,0.0000343754,0.0001163612,0.0001556286,0.00001759218],"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":[0.0006468977,0.0001328578,0.002776679,0.0004875665,0.0002593244,0.0003499617,0.0001139139,0.01510049,0.5287554,0.0154277,0.005929654,0.4300195],"study_design_scores_gemma":[0.00008344675,0.0003710013,0.008210956,0.00004913312,0.0002204746,0.002251033,0.00005686044,0.341604,0.5942104,0.005612843,0.04712354,0.0002062839],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01153898,0.0002403502,0.9822547,0.00009295878,0.0001226651,0.00008977608,0.0002213287,0.003685515,0.001753798],"genre_scores_gemma":[0.1377696,0.0002272174,0.8530475,0.000211271,0.00005193204,0.0001217959,0.0008260921,0.0003944601,0.007349967],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007904988,"threshold_uncertainty_score":0.02644479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04372134657036431,"score_gpt":0.3517603064092902,"score_spread":0.3080389598389259,"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."}}