{"id":"W3022580245","doi":"10.1002/advs.201902307","title":"Multi‐Material 3D and 4D Printing: A Survey","year":2020,"lang":"en","type":"review","venue":"Advanced Science","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":632,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"3D printing; Computer science; Process (computing); Dimension (graph theory); Three dimensional printing; Manufacturing engineering; 3d printed; Computer-aided technologies; Emerging technologies; Nanotechnology; Systems engineering; Engineering; Mechanical engineering; Materials science; Artificial intelligence","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":[0.0006654495,0.0009605258,0.001213301,0.004494896,0.0003368507,0.001418918,0.0009042753,0.001164805,0.006575952],"category_scores_gemma":[0.0006680029,0.000553532,0.0008295129,0.004171722,0.0003938331,0.001760613,0.0006715668,0.00108899,0.003015001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000424758,"about_ca_system_score_gemma":0.000947517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009769272,"about_ca_topic_score_gemma":0.001504609,"domain_scores_codex":[0.9996616,0.0000393748,0.00004666064,0.00006211296,0.0001615987,0.00002866862],"domain_scores_gemma":[0.9995731,0.0002295327,0.00005985298,0.00001751369,0.00009803646,0.00002200174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004718075,0.0001143215,0.0002636007,0.03220092,0.00008083526,0.0003330373,0.00009716851,0.0008483456,0.005553849,0.007531636,0.01471896,0.9382101],"study_design_scores_gemma":[0.000006345258,0.0001129732,0.0005359751,0.002230593,0.00008737267,0.001576131,0.00006606358,0.0003116677,0.003312836,0.001396168,0.9903333,0.00003055432],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004005775,0.9951836,0.0007483658,0.000119173,0.000165189,0.00001181649,0.00003646273,0.00002021845,0.003314543],"genre_scores_gemma":[0.001671153,0.99577,0.0007766139,0.0001213899,0.0001050257,0.00001127139,0.00006067487,0.0000057916,0.001478008],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006575952,"threshold_uncertainty_score":0.0219987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05097390265259097,"score_gpt":0.3092461352628683,"score_spread":0.2582722326102773,"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."}}