{"id":"W4294486664","doi":"10.1002/aic.17904","title":"Generic AI models for mass transfer coefficient prediction in amine‐based CO<sub>2</sub> absorber, Part II: RBFNN and RF model","year":2022,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Beijing Institute of Technology","keywords":"Mass transfer; Amine gas treating; Transfer function; Artificial neural network; Absorption (acoustics); Mass transfer coefficient; Biological system; Computer science; Basis (linear algebra); Radial basis function; Function (biology); Materials science; Chemistry; Mathematics; Artificial intelligence; Engineering; Chromatography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007059389,0.0008673341,0.0005976525,0.0005276544,0.0002319189,0.000491234,0.001012525,0.0009875327,0.0008854399],"category_scores_gemma":[0.001047121,0.0002518924,0.000796881,0.0005170546,0.0002733016,0.0008028172,0.0002854428,0.0005724271,0.0003441203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006033749,"about_ca_system_score_gemma":0.0004671644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007911209,"about_ca_topic_score_gemma":0.005436237,"domain_scores_codex":[0.999779,0.00004941737,0.00001610141,0.00005499358,0.00007111203,0.00002926475],"domain_scores_gemma":[0.9996035,0.0001411964,0.00005769199,0.00002509988,0.0001605465,0.0000120488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005000814,0.00003970934,0.0009120592,0.00007402574,0.00003792251,0.00003333243,0.00002424057,0.9638358,0.006305639,0.001028571,0.0003214744,0.02733721],"study_design_scores_gemma":[7.832713e-7,0.000007023352,0.0001023467,0.000001179314,0.000002955553,0.000002782393,0.000001195585,0.9992385,0.0005042706,0.00007961366,0.00005750715,0.000001798126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1163813,0.0009305999,0.8770441,0.0001624947,0.00007747344,0.00007835259,0.0001783641,0.0009902754,0.004157074],"genre_scores_gemma":[0.9300008,0.0005912134,0.06489477,0.00005752069,0.0000349987,0.0001869978,0.0002904092,0.00005531774,0.003887994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007911209,"threshold_uncertainty_score":0.01573032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01846314468216011,"score_gpt":0.2114068123759725,"score_spread":0.1929436676938124,"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."}}