{"id":"W4411690906","doi":"10.3390/ma18133044","title":"Multi-Response Optimization of Aluminum Laser Spot Welding with Sinusoidal and Cosinusoidal Power Profiles Based on Taguchi–Grey Relational Analysis","year":2025,"lang":"en","type":"article","venue":"Materials","topic":"Welding Techniques and Residual Stresses","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Keyhole; Taguchi methods; Materials science; Welding; Laser; Grey relational analysis; Amplitude; Laser power scaling; Laser beam welding; Acoustics; Optics; Mathematics; Composite material; Statistics","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":[0.001505713,0.0006437196,0.0007997238,0.0007667445,0.0002201139,0.0009479924,0.0005300812,0.0005000639,0.0005399846],"category_scores_gemma":[0.001162765,0.0003282126,0.0008220698,0.0008611259,0.0003087443,0.0003760954,0.0003413276,0.0003290125,0.0001348567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005097988,"about_ca_system_score_gemma":0.0004810039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001360521,"about_ca_topic_score_gemma":0.002087898,"domain_scores_codex":[0.9991645,0.0002130362,0.00006283802,0.0001153577,0.0003895368,0.00005472635],"domain_scores_gemma":[0.9995226,0.0002532507,0.00009282278,0.00002472444,0.0000953709,0.00001135254],"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":[0.0004320337,0.0002802317,0.002196766,0.0009077184,0.00007780171,0.0001414964,0.0003078363,0.2422157,0.6820301,0.0009626138,0.0001300611,0.07031752],"study_design_scores_gemma":[0.00003573703,0.001976269,0.004887529,0.00002572613,0.0001225601,0.00008002169,0.0001687432,0.6763884,0.3149104,0.000540743,0.0008024541,0.0000613736],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7644662,0.001161047,0.2318706,0.00006640162,0.00001770376,0.0002131131,0.0000774332,0.0001961154,0.001931334],"genre_scores_gemma":[0.9473606,0.000438289,0.05146108,0.00001418857,0.00000243511,0.0001323441,0.00003406983,0.00001691518,0.0005400005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001505713,"threshold_uncertainty_score":0.007963121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007438095136583668,"score_gpt":0.2230602508558906,"score_spread":0.2156221557193069,"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."}}