{"id":"W2512987841","doi":"10.1556/1846.2016.00026","title":"Microreactor Mixing-Unit Design for Fast Liquid-Liquid Reactions","year":2016,"lang":"en","type":"article","venue":"Journal of Flow Chemistry","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Microreactor; Chemistry; Slug flow; Mixing (physics); Drop (telecommunication); Toluene; Sodium hydroxide; Flow (mathematics); Chemical engineering; Analytical Chemistry (journal); Thermodynamics; Mechanics; Chromatography; Two-phase flow; Organic chemistry; Mechanical engineering; Physics","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":[0.0003990831,0.0001549286,0.0002004037,0.00007745412,0.00004572964,0.00001539497,0.0001988934,0.0001441625,0.0001164457],"category_scores_gemma":[0.0001456683,0.0001171564,0.0001081069,0.0001851263,0.00005092077,0.0001919219,0.00001492618,0.0001939286,0.000005313126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001945991,"about_ca_system_score_gemma":0.00007832009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.601342e-7,"about_ca_topic_score_gemma":1.109036e-8,"domain_scores_codex":[0.9990259,0.00000700972,0.000542704,0.0000929447,0.0001297063,0.0002016737],"domain_scores_gemma":[0.9990091,0.00009830806,0.0002010445,0.0001666515,0.0004709249,0.00005392783],"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":[0.000148748,0.00002268001,0.000003507735,0.00007668944,0.00006620046,0.000004759552,0.00003636939,0.00001935833,0.9715453,0.00003012467,0.02585206,0.002194187],"study_design_scores_gemma":[0.0004516384,0.0001258193,0.000004555254,0.0001857795,0.00002150523,0.0001579468,0.00002938474,0.00005623344,0.9316437,0.00005976741,0.06712919,0.0001344733],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1420696,0.0001294993,0.8562319,0.0002177663,0.0002445244,0.00008758374,0.00003520757,0.00009032051,0.0008936652],"genre_scores_gemma":[0.9727492,0.00007887569,0.02505209,0.00005442966,0.0008331221,0.00001925083,0.00001392242,0.00006167589,0.001137399],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8311797,"threshold_uncertainty_score":0.4777498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02129606931624895,"score_gpt":0.2473264759092538,"score_spread":0.2260304065930049,"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."}}