{"id":"W1980739201","doi":"10.1016/j.nima.2004.07.212","title":"Straw tube tracking detector (STT) for ZEUS","year":2004,"lang":"en","type":"article","venue":"Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"ZEUS (particle detector); Detector; Tracking (education); Tube (container); Computer science; Physics; Engineering; Optics; Mechanical engineering; Psychology","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":[0.001452964,0.001371452,0.001864348,0.002933643,0.00208679,0.001726905,0.002220844,0.002445412,0.07375216],"category_scores_gemma":[0.001750516,0.001481166,0.001030875,0.002351675,0.0008516472,0.003003094,0.002008855,0.001736128,0.02215541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001866716,"about_ca_system_score_gemma":0.002590468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001658485,"about_ca_topic_score_gemma":0.004644501,"domain_scores_codex":[0.9985455,0.0001465228,0.00005444941,0.0005719489,0.000498288,0.0001833403],"domain_scores_gemma":[0.9987428,0.0002318309,0.0001693123,0.0003264925,0.0003935754,0.0001360861],"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":[0.004381327,0.0001720202,0.0147614,0.001217412,0.0004005173,0.0007800604,0.0004375364,0.003116682,0.692012,0.05814309,0.1078875,0.1166905],"study_design_scores_gemma":[0.0003894869,0.0006159182,0.009510335,0.0001193673,0.0003297506,0.001435095,0.0001628353,0.02000344,0.555299,0.007430781,0.4045019,0.0002021047],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1394598,0.003702432,0.5638654,0.002644616,0.001396001,0.001498196,0.04162038,0.08300631,0.1628068],"genre_scores_gemma":[0.3626426,0.001529489,0.3793984,0.002623028,0.0002768461,0.001525213,0.04198145,0.009162268,0.2008608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07375216,"threshold_uncertainty_score":0.2467256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06586464900082277,"score_gpt":0.3889487253333207,"score_spread":0.3230840763324979,"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."}}