{"id":"W3035837250","doi":"10.17615/0xnd-h270","title":"$α$-event Characterization and Rejection in Point-Contact HPGe Detectors","year":2020,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Chemical and Physical Properties of Materials","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Pacific Northwest National Laboratory; Lawrence Berkeley National Laboratory; Nuclear Physics; Natural Sciences and Engineering Research Council of Canada; Oak Ridge National Laboratory; Los Alamos National Laboratory; Alexander von Humboldt-Stiftung; Deutsche Forschungsgemeinschaft; Laboratory Directed Research and Development; U.S. Department of Energy; Office of Science; Russian Foundation for Basic Research; National Science Foundation","keywords":"Semiconductor detector; Characterization (materials science); Event (particle physics); Detector; Point (geometry); Physics; Nuclear physics; Optics; Astrophysics; Mathematics; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001202308,0.0004561695,0.0006079629,0.0008715471,0.0004937294,0.001725765,0.001297787,0.001207278,0.00351227],"category_scores_gemma":[0.002074393,0.0004284389,0.0003977588,0.0008278689,0.0004543361,0.0008445901,0.0004890824,0.0006503426,0.001033779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004468571,"about_ca_system_score_gemma":0.0001703611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007501649,"about_ca_topic_score_gemma":0.00099666,"domain_scores_codex":[0.9986607,0.0003500154,0.00003808765,0.0003014121,0.0005234975,0.0001262833],"domain_scores_gemma":[0.9983245,0.0008312236,0.0002149478,0.0002794377,0.0002955695,0.00005431668],"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":[0.004483263,0.0001799464,0.02282228,0.0002366853,0.0001433617,0.0007670868,0.000747416,0.00224534,0.9220498,0.002699185,0.001064716,0.042561],"study_design_scores_gemma":[0.00007169224,0.0007142919,0.05547902,0.00003370559,0.00009179849,0.001636428,0.0002666303,0.01849923,0.9174758,0.001064976,0.004616471,0.000050021],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8835931,0.001801927,0.1017431,0.0001745266,0.00004201978,0.00007432889,0.000366307,0.001276972,0.01092768],"genre_scores_gemma":[0.9858987,0.000278344,0.008087683,0.00008923175,0.00001760061,0.00002027095,0.0002921118,0.000210968,0.005105133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00351227,"threshold_uncertainty_score":0.01174968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01331625292903255,"score_gpt":0.1939205557569587,"score_spread":0.1806043028279262,"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."}}