{"id":"W571326948","doi":"10.1016/b978-0-444-63578-5.50072-4","title":"An Approximate Modelling Method for Industrial l-lysine Fermentation Process","year":2015,"lang":"en","type":"book-chapter","venue":"Computer-aided chemical engineering/Computer aided chemical engineering","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Process (computing); Bayesian network; Fermentation; Multivariate statistics; Imputation (statistics); Computer science; Conditional independence; Process engineering; Missing data; Machine learning; Chemistry; Artificial intelligence; Engineering; Food science","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":[0.0005123499,0.0005554283,0.0009887876,0.0002989011,0.0004460051,0.0007595974,0.001119318,0.0009198542,0.002422181],"category_scores_gemma":[0.0007544707,0.0003159597,0.001058481,0.0004883175,0.0002852521,0.0006703862,0.0005577591,0.0006797574,0.0005369874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005966381,"about_ca_system_score_gemma":0.0007858857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009052817,"about_ca_topic_score_gemma":0.004936277,"domain_scores_codex":[0.9997527,0.00007079368,0.0000160215,0.00004471856,0.00009626269,0.0000194712],"domain_scores_gemma":[0.9997701,0.0001148961,0.00001748119,0.00001702648,0.00007308846,0.00000737306],"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":[0.00004562955,0.00002140822,0.0001810082,0.0001348902,0.00002531445,0.00004473701,0.00004823676,0.9428192,0.004661106,0.006132572,0.0003926437,0.04549318],"study_design_scores_gemma":[0.000001352716,0.000007335689,0.0000252068,0.00000207548,0.000003306227,0.000005620135,0.000002221549,0.9985358,0.0003021785,0.0006755653,0.0004374237,0.000001952064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00547416,0.0002850881,0.9913731,0.00004368104,0.00003409577,0.0000199266,0.00003621524,0.0001712362,0.002562621],"genre_scores_gemma":[0.6357954,0.001137927,0.3468658,0.0001017039,0.00008368449,0.0003982195,0.0003036129,0.0002626216,0.01505109],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009052817,"threshold_uncertainty_score":0.01800025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04465391413712568,"score_gpt":0.285206408394412,"score_spread":0.2405524942572863,"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."}}