{"id":"W4365149956","doi":"10.1002/cjce.24913","title":"Hierarchical‐linked batch‐to‐batch optimization based on transfer learning of synthesis process","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Process Optimization and Integration","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Central University Basic Research Fund of China; Six Talent Peaks Project in Jiangsu Province; National Natural Science Foundation of China","keywords":"Computer science; Batch processing; Process (computing); Process optimization; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0002586424,0.0001286332,0.000194787,0.000381065,0.00004398408,0.00003514158,0.0002308917,0.00008822238,0.00006924914],"category_scores_gemma":[0.0006237024,0.0001061474,0.00007238756,0.0007122235,0.00002328018,0.0000912473,0.000002529172,0.0003977046,0.000004795334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001124117,"about_ca_system_score_gemma":0.0001589081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002643053,"about_ca_topic_score_gemma":0.00001147614,"domain_scores_codex":[0.9991429,0.00001430632,0.000330905,0.00007416803,0.000211626,0.0002261307],"domain_scores_gemma":[0.999289,0.0001658635,0.00002965998,0.0000901478,0.0001514154,0.0002739062],"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":[0.00001042508,0.000002974574,0.00001353447,0.00006538046,0.00001736538,0.000002990576,0.0003409209,0.9906848,0.008041541,0.00007954609,0.00007943463,0.0006611042],"study_design_scores_gemma":[0.0001256735,0.00002555399,0.00002122819,0.0001900164,0.00001583734,0.000003834052,0.00001951059,0.9186752,0.08067491,0.00001366752,0.000130838,0.0001037692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3801086,0.00007386224,0.6152505,0.002324163,0.0004087464,0.000269416,0.00001867316,0.000266953,0.001279101],"genre_scores_gemma":[0.9985366,0.000005363729,0.001264443,0.00005436312,0.00007254135,0.000009719582,0.000006164707,0.00004049656,0.0000103261],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.618428,"threshold_uncertainty_score":0.4328564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00770048382121034,"score_gpt":0.1945431244080757,"score_spread":0.1868426405868654,"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."}}