{"id":"W4322626053","doi":"10.1007/s13632-023-00939-1","title":"Effects of Fe-Addition as a Beneficial Modifying Element on the Microstructure and Mechanical Properties of an Al–Si–Cu–Mg–Ni–Mn Piston Alloy","year":2023,"lang":"en","type":"article","venue":"Metallography Microstructure and Analysis","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Microstructure; Materials science; Alloy; Intermetallic; Scanning electron microscope; Metallurgy; Differential scanning calorimetry; Piston (optics); Transmission electron microscopy; Ultimate tensile strength; Composite material; Nanotechnology","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":[0.0001290317,0.0002031157,0.0001675661,0.0001675775,0.0001658975,0.0001785588,0.0002548557,0.0002114964,0.001083196],"category_scores_gemma":[0.0002304399,0.0001762608,0.0001060505,0.0001499613,0.0002013625,0.0001470279,0.0001158199,0.0001589859,0.0001182498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001696531,"about_ca_system_score_gemma":0.0001346395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001566161,"about_ca_topic_score_gemma":0.003138775,"domain_scores_codex":[0.9999208,0.00001086028,0.000009713933,0.00001838693,0.00002266914,0.0000176338],"domain_scores_gemma":[0.9998612,0.00002948767,0.00003711012,0.00001403375,0.00003484941,0.00002331041],"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":[0.0004570046,0.00002857582,0.0003116647,0.00003032993,0.000006667343,0.00005195938,0.00001501667,0.0002970887,0.9978729,0.00002463124,0.0000121039,0.0008920386],"study_design_scores_gemma":[0.000009899139,0.0001983961,0.003121229,0.000001584241,0.00001596558,0.00002939999,0.00001277681,0.001255219,0.9950939,0.000005415421,0.0002530433,0.000003078841],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993201,0.0001189796,0.0001998757,0.000007853224,0.000004969516,0.000003346069,0.00002155298,0.00001098915,0.0003122888],"genre_scores_gemma":[0.9991767,0.00004815132,0.0003418661,0.000005383564,0.000001750299,0.000001772246,0.0000182815,0.000004989764,0.0004010654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001566161,"threshold_uncertainty_score":0.003623664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007832329445545318,"score_gpt":0.1998108360919808,"score_spread":0.1919785066464355,"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."}}