{"id":"W2176726395","doi":"10.1109/rtc.2007.4382848","title":"The TIGRESS DAQ/Trigger system","year":2007,"lang":"en","type":"article","venue":"","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Data acquisition; Detector; Computer hardware; Computer science; Nuclear electronics; SIGNAL (programming language); Telecommunications","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":[0.001491909,0.001058712,0.00081738,0.001698031,0.0008403386,0.001562564,0.003068486,0.0008834036,0.09270635],"category_scores_gemma":[0.001472248,0.0007760711,0.0004624457,0.001162792,0.0003977678,0.001089581,0.001735335,0.001456032,0.04780758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001584039,"about_ca_system_score_gemma":0.001513049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002001442,"about_ca_topic_score_gemma":0.002180204,"domain_scores_codex":[0.9987121,0.00008790282,0.00008067892,0.0003559265,0.0005863047,0.0001770224],"domain_scores_gemma":[0.9989579,0.00007316152,0.00009039568,0.0003386425,0.0004261287,0.0001138291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002967967,0.0002694432,0.008652443,0.0007785922,0.0002766712,0.0007738375,0.000427337,0.004292863,0.2966437,0.03037163,0.4642224,0.190323],"study_design_scores_gemma":[0.0005506224,0.0005972921,0.006239375,0.00008413321,0.00008256111,0.001598938,0.00009400322,0.03450616,0.1996675,0.005009959,0.7512682,0.0003011737],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.06139451,0.001112567,0.3334663,0.000888703,0.000965638,0.002366663,0.07641855,0.3828743,0.1405129],"genre_scores_gemma":[0.2799451,0.0008029459,0.3905009,0.002615393,0.0008419384,0.004403517,0.1398828,0.02612309,0.1548844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09270635,"threshold_uncertainty_score":0.3101336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0082628300700948,"score_gpt":0.2327418814079717,"score_spread":0.2244790513378769,"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."}}