{"id":"W2138108986","doi":"10.1002/bit.24562","title":"Improving piezoelectric cell printing accuracy and reliability through neutral buoyancy of suspensions","year":2012,"lang":"en","type":"article","venue":"Biotechnology and Bioengineering","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Microfluidics; Materials science; Nozzle; Reproducibility; Drop (telecommunication); Piezoelectricity; Ficoll; Suspension (topology); Repeatability; Neutral buoyancy; Nanotechnology; Buoyancy; Inkwell; Chromatography; Chemistry; Composite material; Mechanical engineering; Engineering; Mechanics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003671868,0.0001747349,0.0002243341,0.0001881006,0.00007050487,0.00001317616,0.0001548147,0.0003827154,0.000007125687],"category_scores_gemma":[0.0003961607,0.0001641313,0.00003223895,0.0004228368,0.0002025758,0.0001769938,0.0002306896,0.0005649356,0.000003127353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003050949,"about_ca_system_score_gemma":0.00001121925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000284779,"about_ca_topic_score_gemma":9.100999e-7,"domain_scores_codex":[0.9988279,0.00001403291,0.0002720988,0.0002083664,0.00009537808,0.0005822217],"domain_scores_gemma":[0.9993463,0.0002232233,0.00003923761,0.0002613003,0.00002521596,0.0001047629],"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":[0.000005845514,0.00005709491,0.01685932,0.0008742556,0.00003293332,0.000003530628,0.0001922582,0.0003305482,0.916745,0.002862903,0.0000289509,0.06200735],"study_design_scores_gemma":[0.0003327029,0.00007707455,0.01638032,0.00007580601,0.00002955412,0.00004459887,0.00007797906,0.0483695,0.9324816,0.0001617819,0.001622419,0.000346701],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.969979,0.003271232,0.02560788,0.0001671105,0.0001875793,0.0001601905,0.000001935774,0.0004538918,0.0001711498],"genre_scores_gemma":[0.9840415,0.0009655207,0.0148876,0.000005675283,0.00005634989,0.000008373218,0.000001310694,0.00002546799,0.000008207976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06166065,"threshold_uncertainty_score":0.669308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026729701220122,"score_gpt":0.2350201126086493,"score_spread":0.2247528155964481,"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."}}