{"id":"W4389639571","doi":"10.1016/j.compscitech.2023.110393","title":"Additive manufacturing of hybrid piezoelectric/magnetic self-sensing actuator using pellet extrusion and immersion precipitation with statistical modelling optimization","year":2023,"lang":"en","type":"article","venue":"Composites Science and Technology","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Materials science; Actuator; Extrusion; Composite material; Piezoelectricity; Vibration; 3D printing; Fabrication; Mechanical engineering; Computer science; Acoustics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001652972,0.0001437294,0.0001693357,0.0007855029,0.0002721051,0.00004219085,0.000124759,0.00006451905,0.000003283286],"category_scores_gemma":[0.00004826319,0.000130819,0.000007649014,0.0006966554,0.0005367836,0.0001706126,0.0001590016,0.0001656648,0.000001461236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005470769,"about_ca_system_score_gemma":0.0000252079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006775479,"about_ca_topic_score_gemma":3.744688e-7,"domain_scores_codex":[0.9990659,0.00001034056,0.000155681,0.0003043459,0.0001766102,0.0002871279],"domain_scores_gemma":[0.9995199,0.0001397559,0.00005673194,0.000142846,0.0001030638,0.00003763111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002910515,0.0000236867,0.0002564689,0.0001562456,0.00003164116,0.00003463221,0.000383778,0.5678262,0.1190816,0.001025037,0.00003669413,0.311115],"study_design_scores_gemma":[0.0001025838,0.0001058486,0.00008638794,0.00005504038,0.00001462792,0.00003885538,0.0001694432,0.66196,0.3366796,0.0006752654,0.00000864431,0.0001037065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6481103,0.00007583883,0.3510703,0.00002844022,0.00002438196,0.0001009143,0.000006117693,0.0005524078,0.00003140981],"genre_scores_gemma":[0.8708047,0.0002292463,0.1289319,0.000002218111,0.000005986534,0.000002417225,0.000007862555,0.00001420299,0.0000014448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3110113,"threshold_uncertainty_score":0.5334646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00955124190093395,"score_gpt":0.2080959234874285,"score_spread":0.1985446815864946,"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."}}