{"id":"W4408377877","doi":"10.5267/j.ijiec.2025.1.005","title":"Research on workload balance problem of mixed model assembly line under parallel task strategy","year":2025,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Beijing Wuzi University; National Natural Science Foundation of China","keywords":"Workload; Task (project management); Balance (ability); Assembly line; Computer science; Line (geometry); Mathematical optimization; Operations research; Parallel computing; Operations management; Engineering; Mathematics; Medicine; Mechanical engineering; Physical medicine and rehabilitation; Systems 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":[0.0005590983,0.0001646318,0.0002801135,0.0009844138,0.00004012788,0.00007545703,0.0004566575,0.0001675795,0.000004316151],"category_scores_gemma":[0.0001720888,0.0001722556,0.0001010303,0.0006524641,0.00002702839,0.0002110346,0.00004540474,0.000770525,0.000003462155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003098894,"about_ca_system_score_gemma":0.0002991471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007243616,"about_ca_topic_score_gemma":0.000002514731,"domain_scores_codex":[0.998167,0.0000471059,0.0008026562,0.0001284593,0.0006395851,0.0002151795],"domain_scores_gemma":[0.998104,0.0004629022,0.0001701491,0.0001217112,0.001069535,0.00007167936],"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":[0.00005035078,0.00007796854,0.00006357005,0.0000154934,0.0002462629,0.000006605643,0.00004056605,0.9866491,0.001890285,0.006897216,0.001292155,0.002770457],"study_design_scores_gemma":[0.001207069,0.00008935774,0.000345886,0.0007745837,0.00002000206,0.000009339617,0.00005290161,0.994977,0.001108425,0.001134104,0.0001631134,0.0001182164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07518185,0.0001552513,0.9217553,0.0005112782,0.001211918,0.0001607277,0.00002251529,0.00007709069,0.0009240476],"genre_scores_gemma":[0.975691,0.00006405786,0.02371308,0.00001418473,0.0003929352,0.000007885408,0.00002358235,0.00002798413,0.00006528414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9005092,"threshold_uncertainty_score":0.7024381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0584162640161402,"score_gpt":0.3353054030436989,"score_spread":0.2768891390275587,"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."}}