{"id":"W4235918348","doi":"10.1115/1.4051884","title":"Development of Intertwined Infills to Improve Multi-Material Interfacial Bond Strength","year":2021,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Slicing; Interlacing; Tracing; Computer science; Material properties; Material efficiency; Material flow; Process (computing); Interlocking; Joint (building); Mechanical engineering; Engineering drawing; Materials science; Structural engineering; Engineering; Artificial intelligence; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002592359,0.0005201116,0.000330461,0.000811992,0.0001458896,0.0004221204,0.0005333732,0.0004089779,0.001160094],"category_scores_gemma":[0.0005666372,0.000294884,0.0003116588,0.0002962894,0.0001942048,0.0005011311,0.0004219132,0.0004176688,0.0004570832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001910427,"about_ca_system_score_gemma":0.0002407913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002222675,"about_ca_topic_score_gemma":0.0008535799,"domain_scores_codex":[0.9997738,0.00001742832,0.00001877609,0.00005228853,0.0001030664,0.00003462022],"domain_scores_gemma":[0.9995672,0.00005285342,0.0001611524,0.00005505644,0.000109444,0.00005438793],"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":[0.00003781839,0.00009920658,0.000534291,0.0001567041,0.00001584433,0.0001705076,0.00004263588,0.005177297,0.9755219,0.0007210972,0.0002039191,0.01731882],"study_design_scores_gemma":[0.00001803095,0.0004718716,0.001717987,0.00002301034,0.00005186958,0.0001567337,0.00002686338,0.03442074,0.9576887,0.0001407928,0.005264831,0.00001864621],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8437601,0.00234706,0.1438906,0.0001014495,0.0002363442,0.0001358704,0.0001470462,0.00148086,0.007900641],"genre_scores_gemma":[0.9166141,0.0004319881,0.0808292,0.00005261949,0.00001911587,0.000059057,0.0000764791,0.00009216717,0.001825386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001160094,"threshold_uncertainty_score":0.003880858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01084299444151634,"score_gpt":0.2211792751172005,"score_spread":0.2103362806756841,"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."}}