{"id":"W2589125236","doi":"10.1007/s10404-017-1875-x","title":"A simple droplet merger design for controlled reaction volumes","year":2017,"lang":"en","type":"article","venue":"Microfluidics and Nanofluidics","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Waterloo Institute for Nanotechnology, University of Waterloo; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Microfluidics; Volume (thermodynamics); Limit (mathematics); Fabrication; Upstream (networking); Work (physics); Mechanics; Computer science; Nanotechnology; Materials science; Mechanical engineering; Physics; Engineering; Mathematics; Telecommunications","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":[0.0003688954,0.0004991514,0.000569344,0.0002746468,0.0004072057,0.0007962169,0.001282229,0.00076646,0.002064459],"category_scores_gemma":[0.0005236532,0.0005240449,0.0003938122,0.0002385547,0.000327177,0.0008142972,0.000688204,0.000519142,0.0008655483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008330191,"about_ca_system_score_gemma":0.0005775398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003404774,"about_ca_topic_score_gemma":0.000626091,"domain_scores_codex":[0.9994066,0.00005278449,0.00004511186,0.0001453538,0.0003046031,0.00004544617],"domain_scores_gemma":[0.9998057,0.00004344612,0.00004720703,0.00003421337,0.00004570102,0.00002375131],"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":[0.00008971487,0.00004890811,0.00008041353,0.00009994883,0.00001073531,0.00004980306,0.00002346418,0.001338939,0.9801463,0.004280793,0.0003689735,0.01346193],"study_design_scores_gemma":[0.0000610398,0.0002724884,0.000220206,0.000003561525,0.00001685846,0.0001433955,0.00000680448,0.02485868,0.9645479,0.0005014438,0.009340246,0.00002718645],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1930538,0.001816747,0.7893372,0.0006380001,0.0004949752,0.0009060368,0.0003751625,0.002239743,0.01113829],"genre_scores_gemma":[0.5744345,0.0006088932,0.4161868,0.0002049699,0.0001055107,0.0004705213,0.0002247305,0.0001924987,0.007571623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002064459,"threshold_uncertainty_score":0.006906331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02220182540537379,"score_gpt":0.2588296947325245,"score_spread":0.2366278693271507,"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."}}