{"id":"W3171172264","doi":"10.3390/polym13121957","title":"Scientometric Analysis and Systematic Review of Multi-Material Additive Manufacturing of Polymers","year":2021,"lang":"en","type":"review","venue":"Polymers","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scopus; Systematic review; Computer science; Microscale chemistry; Nanotechnology; Materials science; Management science; Data science; Engineering; Mathematics; MEDLINE; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.06392292,0.002574856,0.01156324,0.1059843,0.001738381,0.005132806,0.002636673,0.001959349,0.00412014],"category_scores_gemma":[0.2401122,0.001180865,0.01323934,0.08257364,0.002299398,0.004376087,0.003447252,0.001218877,0.0004933411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007825797,"about_ca_system_score_gemma":0.03848249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01027623,"about_ca_topic_score_gemma":0.02193367,"domain_scores_codex":[0.8703167,0.05575124,0.04299011,0.006867845,0.02272414,0.001350068],"domain_scores_gemma":[0.7214839,0.210564,0.03218,0.006895883,0.02735837,0.00151779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001859069,0.00005038346,0.00849615,0.8895335,0.0282345,0.0004266764,0.001195725,0.0009627248,0.0004262071,0.001926163,0.002598543,0.06596359],"study_design_scores_gemma":[0.0003825515,0.0005604672,0.03073175,0.7303617,0.1648664,0.000890614,0.003240907,0.001951867,0.001235365,0.006994647,0.05852633,0.0002573907],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01504763,0.9577333,0.006439671,0.0016574,0.0004960934,0.007263228,0.00838792,0.0000845861,0.002890127],"genre_scores_gemma":[0.1748255,0.7724509,0.02344486,0.001500948,0.0004118309,0.01950878,0.007051358,0.00006743458,0.0007382909],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8940157,"threshold_uncertainty_score":0.3380608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02572536010457595,"score_gpt":0.2882131049806921,"score_spread":0.2624877448761162,"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."}}