{"id":"W4394616498","doi":"10.4271/2024-01-2428","title":"Parameter Optimization and Characterization of Aluminum-Copper Laser Welded Joints","year":2024,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced Welding Techniques Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Copper; Aluminium; Materials science; Characterization (materials science); Welding; Laser; Metallurgy; Optics; Nanotechnology; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003553957,0.0006135424,0.0007970764,0.0003907902,0.0001215045,0.0001217827,0.0004237837,0.0006755181,0.0003987398],"category_scores_gemma":[0.0002509277,0.0005616768,0.000318816,0.0009678652,0.0004756729,0.0007194124,0.0002152131,0.0007831925,0.00003213441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002078007,"about_ca_system_score_gemma":0.00002771139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007576191,"about_ca_topic_score_gemma":0.001575805,"domain_scores_codex":[0.99703,0.00007196535,0.0009757147,0.0008310844,0.0005351615,0.0005560867],"domain_scores_gemma":[0.9984285,0.0002836952,0.0001147183,0.0008777246,0.00008471168,0.0002106979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004970472,0.00006742689,0.00005245011,0.0001820089,0.000089071,0.00002329588,0.00002237594,0.002042261,0.9902522,0.002083267,0.0007520957,0.004383876],"study_design_scores_gemma":[0.0009957479,0.0014772,0.9220768,0.002026738,0.0007159976,0.0002106792,0.00008477282,0.0003882376,0.02636008,0.005255368,0.03782179,0.002586597],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9658229,0.0006850007,0.001084808,0.002392534,0.0005484954,0.001706023,0.0002300852,0.01302934,0.01450077],"genre_scores_gemma":[0.9724753,0.001573546,0.0248129,0.0002628124,0.00009003829,0.0002165755,0.0001439457,0.0001832785,0.000241573],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9638921,"threshold_uncertainty_score":0.9996835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009018580969124699,"score_gpt":0.2344127886297458,"score_spread":0.2253942076606211,"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."}}