{"id":"W4408102310","doi":"10.1016/j.nima.2025.170382","title":"HSTD13 - Development and application of semiconductor tracking detectors","year":2025,"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":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; TRIUMF","funders":"","keywords":"Semiconductor detector; Tracking (education); Semiconductor; Detector; Optoelectronics; Computer science; Materials science; Psychology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001395141,0.0002511597,0.0003917472,0.0004606226,0.000418274,0.0001587638,0.0001336146,0.0001065935,0.00003232108],"category_scores_gemma":[0.00003621015,0.0002474322,0.0000462289,0.0009785593,0.0001830059,0.000314069,0.0002172216,0.0005030428,8.590721e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000260169,"about_ca_system_score_gemma":0.00007978052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002506104,"about_ca_topic_score_gemma":0.0000212859,"domain_scores_codex":[0.9978575,0.0002975299,0.0005114645,0.0004936656,0.0003213882,0.0005185038],"domain_scores_gemma":[0.9992587,0.0001643067,0.0001795787,0.0001589584,0.0001068102,0.0001316407],"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":[0.00005316511,0.0001516785,0.139862,0.00006469854,0.0001918992,3.161302e-7,0.00159758,0.000003108947,0.3410554,0.0008316679,0.000007252017,0.5161812],"study_design_scores_gemma":[0.00213969,0.0002509553,0.1517556,0.0002239943,0.00003668953,8.567849e-7,0.001860875,0.004422159,0.8325075,0.004517962,0.001795251,0.0004884694],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971846,0.00007416547,0.001418032,0.00002150105,0.0001791515,0.0004514624,0.000006743899,0.00003013116,0.000634214],"genre_scores_gemma":[0.9927129,0.00007857421,0.007005495,0.00001863157,0.00004941443,0.00006804844,0.000007246234,0.00002405234,0.00003560054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5156928,"threshold_uncertainty_score":0.9999978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04443284579432308,"score_gpt":0.380456491190245,"score_spread":0.3360236453959219,"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."}}