{"id":"W2595573636","doi":"10.1039/c7ra02336g","title":"A microfluidic chip integrated with droplet generation, pairing, trapping, merging, mixing and releasing","year":2017,"lang":"en","type":"article","venue":"RSC Advances","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; University of Waterloo","funders":"University of Waterloo","keywords":"Microfluidics; Mixing (physics); Pairing; Microfluidic chip; Trapping; Chip; Nanotechnology; Lab-on-a-chip; Materials science; Chemistry; Computer science; Physics; Telecommunications; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001052718,0.001244336,0.001386104,0.001121937,0.0007614546,0.0009197999,0.002411171,0.001495391,0.00192426],"category_scores_gemma":[0.00088688,0.001081119,0.0007129092,0.0006434424,0.0006247147,0.001164714,0.001367675,0.0009669583,0.001463695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007155201,"about_ca_system_score_gemma":0.001594906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005775273,"about_ca_topic_score_gemma":0.0008846754,"domain_scores_codex":[0.9992111,0.00005926602,0.000068993,0.0002572499,0.0002974806,0.0001059344],"domain_scores_gemma":[0.9994215,0.0001961976,0.00008916741,0.0001078873,0.0001082745,0.00007700484],"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":[0.0001340682,0.0001118671,0.0004279734,0.0003440008,0.00004633729,0.0001394312,0.0000312557,0.0008033959,0.9561481,0.002691438,0.001784512,0.03733751],"study_design_scores_gemma":[0.00005630544,0.0003400105,0.0007785796,0.00001971776,0.00007263079,0.000463823,0.000007637756,0.01044475,0.9675277,0.000359464,0.01985505,0.00007419989],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1349103,0.007220966,0.8342809,0.001336283,0.002156236,0.001687322,0.001733079,0.009302247,0.007372711],"genre_scores_gemma":[0.1897596,0.001771634,0.8008202,0.0006991658,0.0003302238,0.0012139,0.0008738235,0.0001520939,0.004379328],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002411171,"threshold_uncertainty_score":0.006437242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509995028122261,"score_gpt":0.2449033810185218,"score_spread":0.2298034307372992,"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."}}