{"id":"W4407389288","doi":"10.1088/1748-0221/20/02/c02020","title":"Experiences and lessons learned from the End-of-Substructure card production of the ATLAS ITk Strip upgrade","year":2025,"lang":"en","type":"article","venue":"Journal of Instrumentation","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Particle Physics","funders":"CERN","keywords":"Upgrade; Front and back ends; Detector; Computer science; Atlas (anatomy); Large Hadron Collider; Computer hardware; Substructure; Troubleshooting; Converters; Electrical engineering; Physics; Operating system; Telecommunications; Particle physics; Engineering","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":[0.0001020691,0.00004848304,0.00008850807,0.00002395643,0.0000831549,0.00001634907,0.00009696549,0.00001370782,0.00002150629],"category_scores_gemma":[0.00001205113,0.00002697339,0.00004075559,0.0001409862,0.0000761039,0.0001535988,0.00001737108,0.00008794593,1.307577e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001156878,"about_ca_system_score_gemma":0.00007156735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006211718,"about_ca_topic_score_gemma":0.000008341283,"domain_scores_codex":[0.999494,0.00003829626,0.0002313104,0.00005203357,0.0001337149,0.00005061471],"domain_scores_gemma":[0.9995185,0.00003681427,0.0003179254,0.00006675934,0.00004947358,0.00001059566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006962194,0.00002044823,0.7867547,0.000009773988,0.00009729341,5.567448e-8,0.01234781,0.00007359167,0.08573592,0.0007130434,0.0002098633,0.1139679],"study_design_scores_gemma":[0.0002766598,0.00001679694,0.4262547,0.00005226969,0.00002699267,5.279613e-7,0.008886555,0.00004221255,0.562588,0.00155533,0.000273893,0.00002608106],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979052,0.00006417886,0.0000502639,0.001289487,0.0005368121,0.00006252783,0.000004598162,9.41388e-7,0.00008598452],"genre_scores_gemma":[0.9996946,0.00001754625,0.0001499855,0.00001003112,0.00009109954,0.000001931297,0.000002003587,0.000001588073,0.00003118804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4768521,"threshold_uncertainty_score":0.1099943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02400323627838501,"score_gpt":0.2862270805487982,"score_spread":0.2622238442704132,"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."}}