{"id":"W4417213432","doi":"10.1016/j.nima.2025.171227","title":"Improved pixel-wise calibration for charge-integrating hybrid pixel detectors with performance validation","year":2025,"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":true,"ca_institutions":"","funders":"HORIZON EUROPE Marie Sklodowska-Curie Actions; Horizon 2020 Framework Programme; H2020 Marie Skłodowska-Curie Actions; Physicians' Services Incorporated Foundation","keywords":"Pixel; Subpixel rendering; Calibration; Linearity; Image resolution; Energy (signal processing); Detector; Dot pitch","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001504418,0.0003285077,0.0003936439,0.0004293723,0.0007918347,0.0004108413,0.0001563329,0.00009044498,0.00005309626],"category_scores_gemma":[0.00004572304,0.0002912837,0.00007146574,0.0009519809,0.0001269128,0.0006496318,0.0001260088,0.0005746046,8.572583e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003903621,"about_ca_system_score_gemma":0.0001120671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001463227,"about_ca_topic_score_gemma":0.00001500981,"domain_scores_codex":[0.9975545,0.0003195086,0.0004714676,0.0005967852,0.0003323214,0.0007253707],"domain_scores_gemma":[0.9991035,0.0001913964,0.0002030185,0.0001871403,0.0001704547,0.0001444821],"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":[0.0004754959,0.0003033223,0.08117032,0.0001321678,0.0003874512,4.049077e-7,0.001022846,0.00001990529,0.5783697,0.000740013,0.00004425742,0.3373342],"study_design_scores_gemma":[0.004367281,0.001318556,0.01255939,0.0003337664,0.00006807918,0.000001264895,0.0009905447,0.1217689,0.8544742,0.002006976,0.00139973,0.0007113594],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875293,0.00001735125,0.01058185,0.0000585828,0.000306231,0.0009688751,0.00002485777,0.00005788362,0.0004550595],"genre_scores_gemma":[0.9894273,0.0000732969,0.009908277,0.00003378524,0.0001242802,0.0002483791,0.00004010567,0.00004155445,0.0001030577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3366228,"threshold_uncertainty_score":0.9999539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03428212635444312,"score_gpt":0.3524329443743992,"score_spread":0.3181508180199561,"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."}}