{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002384642,0.0001488062,0.0002580206,0.0003089037,0.00005792599,0.00005658642,0.00006582929,0.00009923083,0.0002150032],"category_scores_gemma":[0.00006251845,0.0001201615,0.00003393592,0.0003022654,0.00004781963,0.00006628837,0.00002174614,0.00004857277,0.000001002659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003464674,"about_ca_system_score_gemma":0.0000218806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002720497,"about_ca_topic_score_gemma":0.000007341851,"domain_scores_codex":[0.9992548,0.00007448379,0.0002420234,0.0001668786,0.0001318303,0.0001300139],"domain_scores_gemma":[0.9995757,0.000128242,0.00006018756,0.0001512132,0.00005542453,0.00002917097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005862465,0.00004151714,0.00334858,0.00008468563,0.0001427738,0.000005494272,0.00003896766,0.9438093,0.05167061,0.00005165034,0.0002014219,0.00001870629],"study_design_scores_gemma":[0.0005953764,0.0001048659,0.04182415,0.0002442367,0.0001594108,0.000001135459,0.00002301736,0.05964431,0.8970827,0.000009853201,0.0001159464,0.0001949582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609083,0.00002495502,0.03818918,0.00007774276,0.00007511734,0.0002079488,0.0001313009,0.0001638773,0.0002215539],"genre_scores_gemma":[0.9645364,0.000005554912,0.03520264,0.00002348514,0.00001082952,0.0000244292,0.00005189859,0.00001817473,0.0001266218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.884165,"threshold_uncertainty_score":0.4900042,"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."}}