{"id":"W4205883012","doi":"10.1016/j.bprint.2021.e00189","title":"Review of extrusion-based multi-material bioprinting processes","year":2022,"lang":"en","type":"article","venue":"Bioprinting","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scaffold; Extrusion; Biofabrication; 3D bioprinting; Process (computing); Tissue engineering; Nanotechnology; Materials science; Computer science; Biomedical engineering; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0015095,0.0001868278,0.0003159187,0.0002026763,0.0002069904,0.00002976204,0.0005942078,0.00005302663,0.001744206],"category_scores_gemma":[0.001548833,0.0001937241,0.00009514578,0.0009230721,0.00008841794,0.00005599375,0.0005955789,0.0003705364,0.00002810924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001025154,"about_ca_system_score_gemma":0.0001359392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004017006,"about_ca_topic_score_gemma":0.000001291724,"domain_scores_codex":[0.99793,0.00008364594,0.0006142626,0.0002942815,0.0006105537,0.0004672226],"domain_scores_gemma":[0.9990213,0.0002080329,0.0001375577,0.0003750725,0.0001538199,0.0001042321],"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":[0.00003536519,0.0003816009,0.01312152,0.1303138,0.0001183609,0.00004213114,0.0002695296,0.004411475,0.721545,0.0001686987,0.001613197,0.1279792],"study_design_scores_gemma":[0.001518922,0.0001594213,0.00528259,0.02002464,0.00006831046,0.00004146173,0.0003148413,0.09159477,0.7212482,0.00005925123,0.1582806,0.001406987],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618318,0.01990882,0.009005639,0.0004803401,0.00187148,0.001298311,0.00009138844,0.00154039,0.003971797],"genre_scores_gemma":[0.9853582,0.001034546,0.01302308,0.0001730655,0.0001219456,0.0001411559,0.00002661471,0.00007004062,0.00005132096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1566674,"threshold_uncertainty_score":0.9991683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02833120540096283,"score_gpt":0.2861585813917393,"score_spread":0.2578273759907764,"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."}}