{"id":"W4407180700","doi":"10.1007/s11666-025-01934-4","title":"Aeroacoustic Process Monitoring and Anomaly Detection in Cold Spray Additive Manufacturing","year":2025,"lang":"en","type":"article","venue":"Journal of Thermal Spray Technology","topic":"Combustion and flame dynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Standards and Technology; U.S. Department of Commerce","keywords":"Materials science; Anomaly detection; Gas dynamic cold spray; Manufacturing process; Process (computing); Spray drying; Spray forming; Metallurgy; Nanotechnology; Composite material; Engineering; Computer science; Data mining; Chemical engineering; Coating","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002929642,0.0002617213,0.0001929525,0.0006252004,0.0001149601,0.0002708544,0.0002929896,0.0003314612,0.0003921722],"category_scores_gemma":[0.0005008546,0.0001411748,0.0001504698,0.0003660057,0.000257017,0.000302385,0.0002346905,0.0002582897,0.00009031535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001387389,"about_ca_system_score_gemma":0.00009472456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006458154,"about_ca_topic_score_gemma":0.0006206965,"domain_scores_codex":[0.9996069,0.00004687015,0.00001369271,0.00008197688,0.0002270275,0.00002353024],"domain_scores_gemma":[0.9995258,0.0001823996,0.0001138183,0.00002613338,0.0001357212,0.00001623674],"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":[0.0002666155,0.00006816869,0.01223306,0.0001254192,0.00001961162,0.0002765328,0.0001983401,0.002221411,0.9357933,0.0001226434,0.0001190049,0.0485558],"study_design_scores_gemma":[0.00002260043,0.0008120891,0.1310481,0.00003302363,0.0000567046,0.001005438,0.000346203,0.08157938,0.7829,0.0003215471,0.001826643,0.00004831749],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9600934,0.0005545786,0.03800971,0.00003656907,0.00002264294,0.00002320447,0.00006425507,0.0001774508,0.001018185],"genre_scores_gemma":[0.9925525,0.0001266636,0.006968888,0.0000111674,0.000007513024,0.000008045338,0.00002839883,0.000008556054,0.0002883003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006458154,"threshold_uncertainty_score":0.001549304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00304008891658386,"score_gpt":0.2129786905913779,"score_spread":0.209938601674794,"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."}}