{"id":"W4398763039","doi":"10.58286/29933","title":"Inline Monitoring of continous Ultrasonic Welding Processes of Thermoplastic Composites via a custom polyCMUT based Ultrasound Array","year":2024,"lang":"en","type":"article","venue":"e-Journal of Nondestructive Testing","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Institute for Computing, Information and Cognitive Systems; Bundesministerium für Bildung und Forschung; CMC Microsystems","keywords":"Welding; Ultrasonic welding; Ultrasonic sensor; Materials science; Aerospace; Plastic welding; Piezoelectricity; Mechanical engineering; Friction welding; Ultrasonic testing; Acoustics; Composite material; Engineering; Arc welding; Filler metal; Aerospace engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002163082,0.0003441909,0.000220265,0.0004604491,0.0001337035,0.0002924485,0.0004489453,0.000490696,0.001046571],"category_scores_gemma":[0.0002950727,0.0001793203,0.000167419,0.0004266883,0.0001779286,0.0003229035,0.0002501529,0.0002311879,0.0002787099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001978559,"about_ca_system_score_gemma":0.0001389797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004225669,"about_ca_topic_score_gemma":0.0007092817,"domain_scores_codex":[0.9996845,0.00002605138,0.00001199117,0.00009097629,0.0001603789,0.00002608317],"domain_scores_gemma":[0.9997252,0.0000492113,0.00009689953,0.00002866796,0.00007678766,0.00002329402],"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":[0.0001979998,0.00004929117,0.001521673,0.00008631076,0.000006559025,0.00008991836,0.00008370154,0.0003331938,0.9868023,0.00005612097,0.0001398822,0.01063299],"study_design_scores_gemma":[0.00001571214,0.0006581547,0.01567275,0.00001093095,0.00003608924,0.0002909511,0.00007592684,0.01357211,0.9679921,0.00003569605,0.001613422,0.00002612039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9695768,0.0006969344,0.02674987,0.00005859356,0.00007101839,0.00005545617,0.0002291975,0.0009472037,0.001614891],"genre_scores_gemma":[0.9824985,0.0003508637,0.01444192,0.00005185269,0.0000188992,0.00005859217,0.000129012,0.00005093223,0.002399353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001046571,"threshold_uncertainty_score":0.003501117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01298221265492229,"score_gpt":0.2278514662874213,"score_spread":0.214869253632499,"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."}}