{"id":"W6929094512","doi":"10.48550/arxiv.2003.08339","title":"Embedded Readout Electronics R&D for the Large PMTs in the JUNO Experiment","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Cancer Research and Treatments","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Snolab","funders":"","keywords":"Neutrino; Electronics; Detector; Linearity; Nuclear electronics; Power electronics; Scintillator; Neutrino detector","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000990884,0.0009611515,0.0005436779,0.000386727,0.0004052872,0.0009665157,0.001514073,0.0008206211,0.01096506],"category_scores_gemma":[0.001179414,0.0003751054,0.0003800053,0.0004709541,0.0003648004,0.001182899,0.0007528727,0.0009270232,0.004871206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006554932,"about_ca_system_score_gemma":0.000637248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004480428,"about_ca_topic_score_gemma":0.0005653856,"domain_scores_codex":[0.9989315,0.0001061723,0.00003937539,0.0002317487,0.0005804388,0.000110811],"domain_scores_gemma":[0.99913,0.0001004896,0.00009400611,0.0002399505,0.0003587383,0.00007689212],"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":[0.001038744,0.000318403,0.004793588,0.0007482945,0.0001003938,0.0008208006,0.0002866895,0.002612107,0.7559451,0.01235517,0.02005925,0.2009214],"study_design_scores_gemma":[0.0002183283,0.002256268,0.01125033,0.0001132415,0.0001677676,0.001994625,0.0001071875,0.02215626,0.7119668,0.001746987,0.2479186,0.0001035679],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2504714,0.004274267,0.649627,0.002085329,0.002804348,0.001508033,0.002007755,0.01835716,0.06886463],"genre_scores_gemma":[0.6653683,0.0009703774,0.2762654,0.0009351984,0.0004998158,0.000511491,0.001401622,0.001002186,0.05304563],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01096506,"threshold_uncertainty_score":0.03668177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1026602618981028,"score_gpt":0.2652137725867086,"score_spread":0.1625535106886058,"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."}}