{"id":"W4281727822","doi":"10.1109/tim.2022.3214606","title":"Digital Wire Analyzer of Mechanical Tension, Electrical Continuity, and Isolation","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Office of Science; Syracuse University; University of Wisconsin-Madison; High Energy Physics; U.S. Department of Energy","keywords":"Spectrum analyzer; Voltage; Wire speed; Tension (geology); Acoustics; Vibrating wire; Electrical engineering; Network analyzer (electrical); SIGNAL (programming language); Materials science; Fundamental frequency; Resonance (particle physics); Measuring instrument; Electronic engineering; Engineering; Physics; Computer science; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005724544,0.0005655265,0.0006431193,0.002532802,0.0003138902,0.0007388642,0.0008664593,0.0005208974,0.006401925],"category_scores_gemma":[0.001888848,0.0002596118,0.000157484,0.001929493,0.0003423798,0.0008533811,0.0006544939,0.0004420558,0.001632164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00041664,"about_ca_system_score_gemma":0.000432666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004768085,"about_ca_topic_score_gemma":0.0007846248,"domain_scores_codex":[0.9984311,0.0001470189,0.00006867648,0.0002703041,0.001018296,0.00006446613],"domain_scores_gemma":[0.9984931,0.000377923,0.0001965336,0.0002260775,0.0006220848,0.00008430699],"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":[0.0006182882,0.0002650975,0.01131831,0.0004737904,0.00008835963,0.0003047945,0.0002084618,0.002531119,0.5809674,0.01050735,0.01167023,0.3810469],"study_design_scores_gemma":[0.0001788723,0.001173333,0.04389998,0.0000798477,0.0003202918,0.00409373,0.0002568898,0.1190633,0.7319528,0.004397875,0.09439918,0.000183811],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1239275,0.001426301,0.8325641,0.0001563024,0.0004635789,0.0003154063,0.002681507,0.01140484,0.02706045],"genre_scores_gemma":[0.6242982,0.001168877,0.3451361,0.0003115011,0.0002080843,0.0006833057,0.003100025,0.0005984863,0.02449547],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006401925,"threshold_uncertainty_score":0.0214166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02183139646162163,"score_gpt":0.2306943830073379,"score_spread":0.2088629865457163,"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."}}