{"id":"W4387967513","doi":"10.1016/j.msea.2023.145855","title":"Enhancing microstructure and mechanical properties of laser powder bed fusion-fabricated AlSi10Mg alloy through tailored friction stir processing and post-heat treatment","year":2023,"lang":"en","type":"article","venue":"Materials Science and Engineering A","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Microstructure; Friction stir processing; Ultimate tensile strength; Electron backscatter diffraction; Alloy; Scanning electron microscope; Strengthening mechanisms of materials; Ductility (Earth science); Composite material; Optical microscope; Grain size; Metallurgy","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":[0.0002106216,0.0002153958,0.0002790019,0.0001250768,0.0001709069,0.0002068339,0.00007378198,0.00007218273,0.00001447289],"category_scores_gemma":[0.00006389911,0.0001632241,0.00001101646,0.0002482988,0.0001185563,0.0003511556,0.00008523247,0.00003986627,0.000001859017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003503404,"about_ca_system_score_gemma":0.00002672078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007362873,"about_ca_topic_score_gemma":0.000002747066,"domain_scores_codex":[0.9990135,0.000009777689,0.0002333283,0.0002819052,0.0001606676,0.0003008306],"domain_scores_gemma":[0.9997057,0.00001991879,0.00003001307,0.00009284948,0.00008159258,0.00006998091],"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":[0.0000178761,0.00000445882,0.0000056851,0.0005308139,0.00001039395,0.000002504212,0.001098324,0.00158545,0.9963324,0.000009475902,0.000006089025,0.0003965457],"study_design_scores_gemma":[0.0002031655,0.00008158625,0.002097282,0.0001975602,0.00001937638,0.00002410185,0.0002161718,0.002942636,0.9938683,0.00003048994,0.0001275191,0.0001918395],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987062,0.0003702325,0.0001119884,0.00006098438,0.0002590037,0.0001708989,0.00003626091,0.0002792431,0.000005235899],"genre_scores_gemma":[0.9989075,0.0004505068,0.000489975,0.00001352066,0.00006192565,0.0000271859,0.00001098375,0.0000276883,0.00001072604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002464112,"threshold_uncertainty_score":0.6656087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136974612913807,"score_gpt":0.204061213109928,"score_spread":0.1926914669807899,"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."}}