{"id":"W4401624930","doi":"10.1016/j.jii.2024.100676","title":"Human-Robot Collaboration in Mixed-Flow Assembly Line Balancing under Uncertainty: An Efficient Discrete Bees Algorithm","year":2024,"lang":"en","type":"article","venue":"Journal of Industrial Information Integration","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Key Research and Development Program of Heilongjiang","keywords":"Assembly line; Robot; Line (geometry); Flow (mathematics); Computer science; Flow line; Algorithm; Mathematical optimization; Engineering; Simulation; Artificial intelligence; Mathematics; Mechanical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001123025,0.0002259636,0.0003034487,0.0009044683,0.00008868172,0.0005866256,0.0001464192,0.0003001369,0.00003000945],"category_scores_gemma":[0.0002257939,0.0001981883,0.00008084315,0.0009949927,0.00001899524,0.003667839,0.00001401273,0.0006726566,0.00001462774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008626446,"about_ca_system_score_gemma":0.0002506319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003954818,"about_ca_topic_score_gemma":0.0001161725,"domain_scores_codex":[0.9976593,0.0000984432,0.001434347,0.0001017429,0.0004952454,0.0002108777],"domain_scores_gemma":[0.9988491,0.00007986514,0.0003355139,0.0001317798,0.0005074383,0.00009630741],"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":[0.00002054097,0.00001919859,0.0000141603,0.0000196845,0.00002787858,0.000003510087,0.001187469,0.9553073,0.001802131,0.0004730731,0.001044257,0.04008078],"study_design_scores_gemma":[0.0008162651,0.000234845,0.0001680507,0.0004984586,0.00003326292,0.00002698878,0.002385631,0.9917673,0.003229047,0.0001068315,0.000534162,0.0001991422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1845637,0.000103333,0.8111631,0.0003592992,0.003034634,0.0003189532,0.00003453016,0.0001749678,0.0002474935],"genre_scores_gemma":[0.9880939,0.00002094878,0.01034724,0.00004777093,0.001049342,0.00001262085,0.0003869457,0.00002793491,0.00001333039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8035302,"threshold_uncertainty_score":0.8081883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01768390940399167,"score_gpt":0.2862371201840418,"score_spread":0.2685532107800501,"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."}}