{"id":"W2902408380","doi":"10.1039/c8re00217g","title":"Integrating reactive distillation with continuous flow processing","year":2018,"lang":"en","type":"article","venue":"Reaction Chemistry & Engineering","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University College Dublin; University of Winnipeg","keywords":"Reactive distillation; Process engineering; Continuous flow; Flow (mathematics); Distillation; Computer science; Environmental science; Engineering; Chromatography; Chemistry; Biochemical engineering; Mechanics; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001096672,0.0002103643,0.0001551569,0.00006131078,0.00007320042,0.00004380312,0.00007362205,0.0001098917,0.000022562],"category_scores_gemma":[0.00004060203,0.0002042787,0.00002271405,0.0004910079,0.00004718456,0.0002779703,0.00001243109,0.0002760531,0.000007770457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002817644,"about_ca_system_score_gemma":0.00002263811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003942915,"about_ca_topic_score_gemma":1.388992e-7,"domain_scores_codex":[0.9991969,0.000002190657,0.0002390429,0.0001984225,0.0001421733,0.0002212303],"domain_scores_gemma":[0.9994688,0.00001437467,0.00006529467,0.0001584456,0.0002580833,0.00003500426],"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":[0.000009166014,0.000006252898,0.000039752,0.00007799828,0.00002168692,0.000002118136,0.0001600128,0.0003240646,0.9790091,0.00009936985,0.000175128,0.02007533],"study_design_scores_gemma":[0.0001378529,0.00001946889,0.0001869362,0.0001708742,0.00001225035,0.00006745636,0.0001311572,0.07457438,0.9123915,0.00001144546,0.01205286,0.0002438202],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2134203,0.00005317534,0.7714288,0.00001390958,0.0001197318,0.0001074094,0.000005256309,0.001199393,0.01365205],"genre_scores_gemma":[0.9907905,0.000002341856,0.008474,0.000008117149,0.0004505133,0.00002907503,0.00007916599,0.00005666419,0.0001096074],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7773703,"threshold_uncertainty_score":0.8330243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004837865594149409,"score_gpt":0.2034054677358735,"score_spread":0.198567602141724,"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."}}