{"id":"W4389667498","doi":"10.1109/nssmicrtsd49126.2023.10337858","title":"Data Acquisition Methods for SiPM Characterization: Current Status of the VERA System at TRIUMF","year":2023,"lang":"en","type":"article","venue":"","topic":"Calibration and Measurement Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TRIUMF","funders":"","keywords":"Silicon photomultiplier; Data acquisition; Photomultiplier; Instrumentation (computer programming); Software; Physics; Computer science; Nuclear engineering; Electrical engineering; Optics; Engineering; Detector; Operating system","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":[0.0002937673,0.00005577888,0.00008224487,0.00004083656,0.00003539636,0.00001443777,0.00013266,0.00002628915,0.00003931855],"category_scores_gemma":[0.00002238702,0.0000413507,0.00003054984,0.000182877,0.000006348369,0.0001170709,0.00007196689,0.00002571046,0.00000543697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006742038,"about_ca_system_score_gemma":0.00001280775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000106774,"about_ca_topic_score_gemma":0.00000171622,"domain_scores_codex":[0.9995083,0.00003484904,0.0001675443,0.00008944454,0.00009183508,0.0001080277],"domain_scores_gemma":[0.9995428,0.000033546,0.00002989892,0.000331089,0.00003662552,0.00002601385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001372729,0.00001166134,0.000145273,0.0006469322,0.00002660211,5.945236e-8,0.00010203,0.0001247717,0.9170166,0.004621326,0.019953,0.057338],"study_design_scores_gemma":[0.0002343793,0.00001064195,0.003257931,0.00006809924,0.00002193681,5.620306e-7,0.00003040756,0.1952387,0.3764707,0.00002004153,0.4245586,0.00008806652],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00727739,0.0001253281,0.9880348,0.000101079,0.001063663,0.0006507289,0.000516139,0.001224353,0.001006485],"genre_scores_gemma":[0.9623094,0.0008204544,0.0275945,0.0001196082,0.0004075497,0.0003631409,0.006976705,0.00009366382,0.001314956],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9604403,"threshold_uncertainty_score":0.1686232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1130167641206131,"score_gpt":0.3675252814400771,"score_spread":0.254508517319464,"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."}}