{"id":"W3056914956","doi":"10.1177/1475921720947407","title":"Selective generation of ultrasonic guided waves for damage detection in rectangular bars","year":2020,"lang":"en","type":"article","venue":"Structural Health Monitoring","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Direction Générale de l’Armement; Fonds de recherche du Québec – Nature et technologies; Agence Nationale de la Recherche","keywords":"Laser Doppler vibrometer; Acoustics; Structural health monitoring; Ultrasonic sensor; Finite element method; Bar (unit); Piezoelectricity; Transducer; Lamb waves; Structural engineering; Ultrasonic testing; Modal analysis; Laser scanning vibrometry; Materials science; Optics; Engineering; Surface wave; Physics; Laser","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000125469,0.0001125584,0.0001800395,0.00005864664,0.00007412244,0.00001418947,0.00005688153,0.00005817619,0.000001884716],"category_scores_gemma":[0.0001034932,0.0001182599,0.00003517491,0.0002326446,0.000009044307,0.0001249297,0.000005821324,0.0001436705,3.804834e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002290412,"about_ca_system_score_gemma":0.00003709607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007094443,"about_ca_topic_score_gemma":0.00001911187,"domain_scores_codex":[0.9991415,0.0000263562,0.0003362386,0.0001586642,0.0001072915,0.0002300156],"domain_scores_gemma":[0.9996839,0.00004492955,0.00007215763,0.00006680188,0.00006055722,0.00007170415],"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":[0.00001933262,0.000002157765,0.00136937,0.0004929943,0.00001590814,3.416177e-7,0.001610965,0.1080644,0.8442881,0.00003885536,0.00002357199,0.04407398],"study_design_scores_gemma":[0.000332972,0.0001256806,0.0169767,0.00004732011,0.000004882448,0.000001256772,0.0001599943,0.4740677,0.5079844,0.0001696116,0.00001678862,0.000112623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985252,0.000327762,0.0131364,0.00008729166,0.0006696682,0.0004165698,0.00001509989,0.0000794712,0.00001576115],"genre_scores_gemma":[0.9930446,0.00007327926,0.006256817,0.00001298777,0.0005469008,0.00002422986,0.00001534343,0.00002429765,0.000001541565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3660033,"threshold_uncertainty_score":0.48225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04178542855237065,"score_gpt":0.2907851078187539,"score_spread":0.2489996792663833,"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."}}