{"id":"W3194023761","doi":"10.1016/b978-0-12-819971-8.00001-9","title":"Droplet microfluidics for biomedical devices","year":2021,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Microfluidics; Nanotechnology; Throughput; Materials science; Encapsulation (networking); Computer science; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002862096,0.001404609,0.0008218266,0.001288231,0.0004403252,0.001784888,0.001036941,0.001219428,0.04060144],"category_scores_gemma":[0.0003147034,0.0006665231,0.0004884599,0.001196883,0.0004895203,0.002736835,0.001252058,0.001861898,0.02147346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008056325,"about_ca_system_score_gemma":0.0004707014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004148309,"about_ca_topic_score_gemma":0.0010327,"domain_scores_codex":[0.9997653,0.00001513733,0.00001009153,0.00004731852,0.000145239,0.00001683662],"domain_scores_gemma":[0.9999233,0.00003467665,0.000005432836,0.000009731631,0.00001875197,0.000008066097],"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":[0.00006085319,0.0001233399,0.00007030117,0.001537668,0.00002366896,0.0002745453,0.0002094966,0.001075676,0.08196708,0.1540937,0.1861848,0.5743789],"study_design_scores_gemma":[0.000009865934,0.00002997216,0.00009673185,0.0001820002,0.000007651985,0.0003474314,0.00002141399,0.00104722,0.01033635,0.02486283,0.9630451,0.00001341338],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002511527,0.3689339,0.09239224,0.002637244,0.009193704,0.0001957867,0.0005831604,0.001280864,0.5222715],"genre_scores_gemma":[0.008697422,0.1189441,0.03294703,0.001307542,0.001483276,0.0001788147,0.0004295124,0.0003793275,0.8356329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04060144,"threshold_uncertainty_score":0.1358253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01516343135543375,"score_gpt":0.2402685938940523,"score_spread":0.2251051625386185,"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."}}