{"id":"W4410813562","doi":"10.1016/j.jmatprotec.2025.118912","title":"Quantifying the absorptivity in laser additive manufacturing and welding of aluminum alloy in the conduction mode","year":2025,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Key Research and Development Program of China; University of Toronto; National Natural Science Foundation of China","keywords":"Materials science; Molar absorptivity; Alloy; Aluminium; Laser beam welding; Welding; Laser; Thermal conduction; Mode (computer interface); Metallurgy; Composite material; Optics","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":[0.0003859136,0.0002586961,0.0002159805,0.0005046374,0.0002721749,0.0006272365,0.0004539938,0.0005960662,0.001177899],"category_scores_gemma":[0.0005553788,0.00025808,0.0002825821,0.0004592768,0.0003720963,0.0004480894,0.0002686982,0.0003527637,0.0002408081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00040755,"about_ca_system_score_gemma":0.0003081518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029243,"about_ca_topic_score_gemma":0.001304417,"domain_scores_codex":[0.9997424,0.00003431198,0.000008588578,0.00006197006,0.0001163663,0.00003638286],"domain_scores_gemma":[0.9996773,0.0001524891,0.00005800377,0.00002486825,0.00007033681,0.00001706229],"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":[0.0005108175,0.0000431171,0.002863076,0.00005090014,0.00001641292,0.00006950076,0.00009786981,0.001667129,0.9891523,0.0002115549,0.00004523528,0.005272138],"study_design_scores_gemma":[0.00001132306,0.000195268,0.009472292,0.000005800678,0.00002544516,0.00008254751,0.00009306674,0.008511078,0.9812106,0.00009050124,0.0002904789,0.0000114529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918717,0.0003760584,0.006264258,0.00003003581,0.00000843714,0.00001079165,0.00005348858,0.00007348706,0.001311859],"genre_scores_gemma":[0.9968209,0.0001679018,0.002161135,0.00001677627,0.000002879471,0.000008131449,0.0000402931,0.00001559407,0.0007662784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001177899,"threshold_uncertainty_score":0.003940463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01684503672605578,"score_gpt":0.2670654899546641,"score_spread":0.2502204532286083,"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."}}