{"id":"W4306825741","doi":"10.1088/2631-7990/ac9ba2","title":"Nano-additive manufacturing of multilevel strengthened aluminum matrix composites","year":2022,"lang":"en","type":"article","venue":"International Journal of Extreme Manufacturing","topic":"Aluminum Alloys Composites Properties","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Youth Innovation Promotion Association; Innotech Alberta; Youth Innovation Promotion Association of the Chinese Academy of Sciences; China Association for Science and Technology","keywords":"Materials science; Nanocrystalline material; Microstructure; Aluminium; Deposition (geology); Strengthening mechanisms of materials; Grain size; Composite material; Nanoscopic scale; Matrix (chemical analysis); Nano-; Nanotechnology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002880858,0.0002876569,0.0004070501,0.0005799354,0.0001184002,0.00006710124,0.001114214,0.00005047081,0.0008978108],"category_scores_gemma":[0.00002663395,0.0002865732,0.0002791885,0.00004882891,0.00006533761,0.0004267588,0.0003880602,0.0005146188,0.00001004906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004544975,"about_ca_system_score_gemma":0.00004109921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002914639,"about_ca_topic_score_gemma":0.000004663064,"domain_scores_codex":[0.9974251,0.00007736416,0.0009449417,0.0001832938,0.00107396,0.0002952879],"domain_scores_gemma":[0.9987966,0.000223681,0.0004874344,0.0002021092,0.0001893079,0.0001008684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005668059,0.0002939472,0.0008103515,0.0001036022,0.001999003,0.0005015815,0.002721436,0.5083762,0.4323855,0.0001484626,0.001884026,0.05020913],"study_design_scores_gemma":[0.001061724,0.0001324554,0.002452794,0.0001169956,0.00005191949,0.0005002946,0.0004826062,0.009273075,0.9770873,0.0003212479,0.008204917,0.0003146673],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930806,0.0006237469,0.00248658,0.00009686698,0.002336144,0.0001271712,0.0001163787,0.00008137834,0.001051128],"genre_scores_gemma":[0.995587,0.00007133622,0.003603409,0.00003389024,0.0003742735,0.00001020967,0.00002080028,0.00006425635,0.0002348214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5447018,"threshold_uncertainty_score":0.9999586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01830192515619903,"score_gpt":0.2301892252519767,"score_spread":0.2118873000957777,"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."}}