{"id":"W2208617641","doi":"10.1016/j.ces.2015.12.009","title":"On the scale-up of micro-reactors for liquid–liquid reactions","year":2016,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dissipation; Pressure drop; Sizing; Volumetric flow rate; Mechanics; SCALE-UP; Static mixer; Extraction (chemistry); Drop (telecommunication); Flow (mathematics); Mass transfer; Scale (ratio); Materials science; Chemistry; Analytical Chemistry (journal); Thermodynamics; Chromatography; Electrical engineering; Engineering; Physics","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":[0.0007804668,0.0004310932,0.0004294178,0.0004545752,0.0004126368,0.0008832735,0.0009636511,0.0006413381,0.003628306],"category_scores_gemma":[0.001104662,0.0003137184,0.0006792076,0.0003039298,0.0006862476,0.001677838,0.001009697,0.001226939,0.001432912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007842761,"about_ca_system_score_gemma":0.0004103146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007118135,"about_ca_topic_score_gemma":0.001413397,"domain_scores_codex":[0.9994317,0.00008787342,0.00003205468,0.0001007715,0.0002565469,0.00009114014],"domain_scores_gemma":[0.9996333,0.0001590509,0.00003006129,0.00008021292,0.00006647482,0.00003083987],"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":[0.0003403484,0.0002113814,0.0005098413,0.0005521213,0.00005090405,0.000287681,0.0002166758,0.00626945,0.8353518,0.03386661,0.004027871,0.1183152],"study_design_scores_gemma":[0.00006979489,0.0003617934,0.0009698645,0.00005918718,0.00004979067,0.0001753814,0.00005941928,0.02341733,0.922156,0.008988287,0.0436549,0.00003828502],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6215673,0.0447659,0.2732408,0.008346527,0.002031191,0.0006774637,0.0006207427,0.00181677,0.0469332],"genre_scores_gemma":[0.861287,0.01357187,0.1086906,0.0006827867,0.0003583121,0.0002316055,0.0003296826,0.0001712926,0.01467685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003628306,"threshold_uncertainty_score":0.01213789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01134220338939519,"score_gpt":0.2315038589240947,"score_spread":0.2201616555346995,"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."}}