{"id":"W2762069301","doi":"10.4236/msa.2017.811055","title":"Prediction of Weld Joint Shape and Dimensions in Laser Welding Using a 3D Modeling and Experimental Validation","year":2017,"lang":"en","type":"article","venue":"Materials Sciences and Applications","topic":"Welding Techniques and Residual Stresses","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cégep de Rimouski; Université du Québec à Rimouski","funders":"","keywords":"Materials science; Welding; Joint (building); Taguchi methods; Butt joint; Finite element method; Laser beam welding; Galvanization; Keyhole; Mechanical engineering; Composite material; Structural engineering; Metallurgy; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007585627,0.0006723887,0.0003959017,0.0004755058,0.000282249,0.0006967341,0.0008402517,0.0011278,0.001001353],"category_scores_gemma":[0.001188063,0.0004456989,0.0007009669,0.0004125977,0.0005336915,0.0004635321,0.0005026694,0.0003728552,0.0004292553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006840974,"about_ca_system_score_gemma":0.0007865386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002929079,"about_ca_topic_score_gemma":0.003594064,"domain_scores_codex":[0.9994537,0.0000714015,0.00002567049,0.00007749791,0.0003363333,0.00003541824],"domain_scores_gemma":[0.9993201,0.0002614841,0.00009217974,0.0001906382,0.0001175126,0.0000180465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001741736,0.0001594878,0.005384461,0.000193215,0.00002778633,0.0002198651,0.0004364613,0.7213553,0.2405144,0.001154601,0.0003635709,0.03001676],"study_design_scores_gemma":[0.00001497187,0.0002625068,0.006176314,0.00001355566,0.0000147863,0.0001109475,0.00007008335,0.8571134,0.1346034,0.0003136709,0.001254347,0.00005206096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7222355,0.0002478494,0.2709121,0.00008522471,0.00003131973,0.0001375603,0.000747597,0.001873305,0.003729578],"genre_scores_gemma":[0.9677757,0.000104859,0.03109859,0.000009733693,0.000002019015,0.00008442891,0.000193202,0.0000605686,0.000670852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002929079,"threshold_uncertainty_score":0.005824089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06765669025446962,"score_gpt":0.2915436472200217,"score_spread":0.2238869569655521,"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."}}