{"id":"W2318769149","doi":"10.1016/j.ultras.2016.03.013","title":"Numerical simulation of damage detection using laser-generated ultrasound","year":2016,"lang":"en","type":"article","venue":"Ultrasonics","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":81,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Korea Advanced Institute of Science and Technology; Université de Sherbrooke","keywords":"Ultrasonic sensor; Laser; Nonlinear system; Acoustics; Feature (linguistics); Materials science; Optics; Visualization; Bhattacharyya distance; Dimension (graph theory); Embedding; Computer science; Physics; Artificial intelligence; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001469345,0.0001561854,0.0001759272,0.00006426767,0.00007206004,0.00002774656,0.00008823892,0.000120572,0.00006940023],"category_scores_gemma":[0.0002659814,0.0001254393,0.0000603827,0.000269325,0.00003511745,0.0001915821,0.000005723782,0.00009436735,0.0000148213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001224555,"about_ca_system_score_gemma":0.00002338897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001885541,"about_ca_topic_score_gemma":0.000006619474,"domain_scores_codex":[0.9990645,0.0000302088,0.0003166482,0.0001658199,0.0001893783,0.0002334524],"domain_scores_gemma":[0.9991869,0.0003634893,0.00007800509,0.0001937795,0.0001115652,0.00006631054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005148555,0.00001311931,0.0001924818,0.00001754333,0.00001569167,4.570041e-7,0.00002404815,0.5126467,0.4835542,0.00001401486,0.000006353592,0.003510254],"study_design_scores_gemma":[0.0002567908,0.00002898578,0.0006268093,0.00003740747,0.00002395255,0.000005206282,0.00001216912,0.622647,0.3758958,0.0001169754,0.0002063515,0.0001425755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6290787,0.00003590005,0.3702318,0.000003784106,0.0002081515,0.00008538457,0.0000242095,0.0001250914,0.0002069786],"genre_scores_gemma":[0.9978871,0.00006343507,0.001855894,0.00000778763,0.00009442904,0.000003484955,0.00001085753,0.00004226579,0.00003476892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3688084,"threshold_uncertainty_score":0.5115266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01333926717563851,"score_gpt":0.2256495126417139,"score_spread":0.2123102454660754,"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."}}