{"id":"W4389733903","doi":"10.22323/1.449.0528","title":"Development of the ATLAS Liquid Argon Calorimeter Readout Electronics for the HL-LHC","year":2023,"lang":"en","type":"article","venue":"","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Firmware; Large Hadron Collider; Electronics; Detector; Computer hardware; Calibration; Calorimeter (particle physics); Atlas (anatomy); Data acquisition; Physics; Computer science; Electrical engineering; Embedded system; Nuclear physics; Engineering; Optics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001513402,0.0008148995,0.0006709012,0.0007967345,0.0004045966,0.001679936,0.001722734,0.0006670185,0.02355957],"category_scores_gemma":[0.001492186,0.0004300925,0.0003398643,0.0006464537,0.0002355264,0.0009531743,0.0009342346,0.001056472,0.01198074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009425612,"about_ca_system_score_gemma":0.001277182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001465181,"about_ca_topic_score_gemma":0.001122629,"domain_scores_codex":[0.9981722,0.0001558612,0.00007734622,0.0002207878,0.001171509,0.0002023733],"domain_scores_gemma":[0.9988545,0.0001118241,0.00007643509,0.0001576005,0.0006477846,0.0001518135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003160052,0.0003809789,0.01952378,0.001122223,0.000195313,0.00127144,0.0004267909,0.01302048,0.3659047,0.02149542,0.1271246,0.4463742],"study_design_scores_gemma":[0.0002076463,0.001604545,0.02035337,0.0001576628,0.0001265377,0.001518472,0.0001371706,0.03478071,0.3033539,0.001380048,0.6361298,0.0002501237],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1232981,0.002994946,0.6434018,0.001825447,0.002662063,0.00198745,0.01079845,0.08241666,0.1306152],"genre_scores_gemma":[0.491076,0.001456973,0.360233,0.002542775,0.0007983699,0.001445418,0.01802059,0.00436691,0.1200601],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02355957,"threshold_uncertainty_score":0.07881463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02460274478814087,"score_gpt":0.2588191052779344,"score_spread":0.2342163604897935,"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."}}