{"id":"W2898289001","doi":"10.1177/1475921718808220","title":"Selective generation of ultrasonic guided waves in a bi-dimensional waveguide","year":2018,"lang":"en","type":"article","venue":"Structural Health Monitoring","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":26,"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":"Acoustics; Laser scanning vibrometry; Ultrasonic sensor; Finite element method; Modal; Modal analysis; Lamb waves; Laser Doppler vibrometer; Guided wave testing; Structural health monitoring; Bar (unit); Transducer; Piezoelectricity; Displacement (psychology); Ultrasonic testing; Nondestructive testing; Sensitivity (control systems); Optics; Materials science; Structural engineering; Surface wave; Engineering; Electronic engineering; 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":[0.0001975374,0.000140192,0.0002006247,0.0001251631,0.000102059,0.00001388748,0.00007360745,0.00006468871,0.00001300426],"category_scores_gemma":[0.0000540255,0.0001342272,0.00002997074,0.0002740887,0.0000372569,0.0001299191,0.00001311593,0.0001605276,0.000003433821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003074699,"about_ca_system_score_gemma":0.00008769599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002382675,"about_ca_topic_score_gemma":0.0000534143,"domain_scores_codex":[0.9988217,0.00003323871,0.0004447702,0.0001766122,0.0001958768,0.0003278217],"domain_scores_gemma":[0.999554,0.00004382722,0.00008243857,0.0001210524,0.0001246293,0.00007405796],"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":[0.00002111922,0.00001127841,0.01277627,0.0002994584,0.00003987664,0.000001720744,0.00208019,0.04249057,0.9077663,0.0003529324,0.0003275501,0.0338327],"study_design_scores_gemma":[0.0005351556,0.0001831176,0.1216474,0.000222286,0.000006081344,0.00001577696,0.0001065606,0.3647805,0.5114053,0.0008032262,0.00003686123,0.0002576493],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972379,0.000381981,0.0004856942,0.00005059252,0.001408309,0.0001991965,0.000009363575,0.00006924294,0.0001577164],"genre_scores_gemma":[0.9917474,0.00004711549,0.007215834,0.00001300427,0.0009201256,0.000008163235,0.00001319237,0.00002255703,0.00001256176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.396361,"threshold_uncertainty_score":0.5473626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03226543306139955,"score_gpt":0.3003214477372934,"score_spread":0.2680560146758939,"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."}}