{"id":"W4402174792","doi":"10.36922/ijb.3973","title":"Extrusion bioprinting from a fluid mechanics perspective","year":2024,"lang":"en","type":"article","venue":"International Journal of Bioprinting","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Perspective (graphical); Fluid mechanics; Extrusion; Mechanics; Computer science; Physics; Materials science; Artificial intelligence; Composite material","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003410529,0.0001701815,0.0001830516,0.0004493905,0.00004492135,0.000247456,0.0005647592,0.0001029939,0.0001391032],"category_scores_gemma":[0.0003088992,0.0001542589,0.0001870707,0.0001376114,0.00003038101,0.0002674097,0.0002264956,0.0005292076,0.00006117507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002645063,"about_ca_system_score_gemma":0.00002819513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000424018,"about_ca_topic_score_gemma":0.000002252444,"domain_scores_codex":[0.9987792,0.00001572653,0.0004503096,0.0001805335,0.0003859334,0.0001882333],"domain_scores_gemma":[0.9992524,0.0001676863,0.0001144646,0.0001251897,0.0002956681,0.00004453683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004077838,0.00005533684,0.0004615572,0.00006802317,0.001688796,0.0009757832,0.002440293,0.00867294,0.3713763,0.04758633,0.0009812515,0.5656527],"study_design_scores_gemma":[0.0004115099,0.00005858175,0.001740428,0.001689665,0.00007221656,0.000407939,0.003400071,0.1423074,0.7650746,0.0636466,0.02067659,0.0005144514],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.86928,0.001642574,0.1203186,0.0007551481,0.004533942,0.00004968943,0.00001791874,0.0007769203,0.002625268],"genre_scores_gemma":[0.9893597,0.0002434124,0.009421835,0.00001929378,0.0008842524,0.000001518455,0.000002341747,0.00003651932,0.00003113983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5651382,"threshold_uncertainty_score":0.6290494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111769969832122,"score_gpt":0.249068025781009,"score_spread":0.2379503260826878,"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."}}