{"id":"W4385387357","doi":"10.58286/28130","title":"Automated misalignment correction method for ultrasonic inspection of CFRP parts","year":2023,"lang":"en","type":"article","venue":"Research and Review Journal of Nondestructive Testing","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Position (finance); Computer science; Ultrasonic sensor; Process (computing); Component (thermodynamics); Path (computing); Computer vision; Planar; Orientation (vector space); Artificial intelligence; Acoustics; Computer graphics (images); Mathematics; Physics","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":[0.004580541,0.0001626516,0.0004851249,0.0004761321,0.000162114,0.00002669995,0.0001647359,0.00007023112,0.00000322028],"category_scores_gemma":[0.005239589,0.0001393089,0.00009049607,0.001452228,0.0001434172,0.0002121335,0.00004330488,0.0004680219,0.00000154199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002653605,"about_ca_system_score_gemma":0.0001110161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001984861,"about_ca_topic_score_gemma":0.000001690036,"domain_scores_codex":[0.9980518,0.0002668201,0.0006776781,0.0001746827,0.0004526312,0.0003764519],"domain_scores_gemma":[0.995551,0.002610173,0.000306776,0.0001456529,0.001255896,0.0001305362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001925912,0.0001952489,0.02221169,0.02254555,0.0007770712,0.0001097885,0.0007217532,0.001412117,0.6418422,0.003842262,0.03231804,0.2738317],"study_design_scores_gemma":[0.003768734,0.01077002,0.1292255,0.09043299,0.0006346865,0.009935522,0.00158775,0.2088895,0.1433725,0.3981642,0.001354061,0.001864501],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8353912,0.04713026,0.100537,0.0003860864,0.002249702,0.004501998,0.00005222875,0.00496177,0.004789799],"genre_scores_gemma":[0.296205,0.01153019,0.6918207,0.000007543113,0.0002848154,0.00006600445,0.000004945795,0.00007191396,0.000008871227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5912837,"threshold_uncertainty_score":0.6272656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1093800522486721,"score_gpt":0.4210941022199765,"score_spread":0.3117140499713044,"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."}}