{"id":"W3005314474","doi":"10.3390/app10030943","title":"Topology Optimization for Multipatch Fused Deposition Modeling 3D Printing","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Science Foundation of Hunan Province; National Natural Science Foundation of China","keywords":"Topology optimization; Fused deposition modeling; Topology (electrical circuits); Interpolation (computer graphics); Deposition (geology); Layer (electronics); Computer science; Asynchronous communication; Zigzag; 3D printing; Mathematical optimization; Materials science; Nanotechnology; Engineering; Mathematics; Mechanical engineering; Frame (networking); Finite element method; Geometry","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":[0.0003505362,0.0004943383,0.0005272261,0.0004038082,0.0003265021,0.0006632873,0.000821022,0.000963121,0.00164908],"category_scores_gemma":[0.0004469723,0.0004414595,0.0008178304,0.0003596948,0.0004418373,0.0005852693,0.0006993499,0.0005833023,0.0002842755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005582468,"about_ca_system_score_gemma":0.0006667884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001729593,"about_ca_topic_score_gemma":0.001727218,"domain_scores_codex":[0.9998415,0.00003574263,0.00000635054,0.00002491518,0.0000767676,0.00001475959],"domain_scores_gemma":[0.9998616,0.0000646321,0.00002004836,0.00001991026,0.00002431318,0.000009546382],"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":[0.000009959659,0.00001059978,0.0001418647,0.00003575266,0.00001129988,0.0000448482,0.00002518784,0.9772414,0.005552536,0.007867882,0.000170764,0.008887909],"study_design_scores_gemma":[0.000001507426,0.00000374787,0.00002132536,0.000001604482,0.000001305196,0.000009056642,0.00000229696,0.9983047,0.0005007743,0.0007486695,0.0004030608,0.000001879294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01369691,0.0001750996,0.9814092,0.00006834118,0.00002088843,0.00002320165,0.00004513454,0.0001540808,0.004407112],"genre_scores_gemma":[0.5489558,0.000402026,0.4451816,0.00005900094,0.00002364474,0.0002342095,0.0001351362,0.000186483,0.004822164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001729593,"threshold_uncertainty_score":0.005516708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02373380688237872,"score_gpt":0.2339661821718172,"score_spread":0.2102323752894385,"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."}}