{"id":"W173371885","doi":"","title":"Integrating product modularization and assembly line reconfiguration decisions: a genetic algorithm approach","year":2006,"lang":"en","type":"article","venue":"international conference on Modelling and simulation","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Control reconfiguration; Modular programming; Modular design; Computer science; Genetic algorithm; Product (mathematics); Mathematical optimization; Product line; Integer (computer science); Algorithm; Engineering; Mathematics; Manufacturing engineering; Embedded system; Programming language; Machine learning","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":[0.001000541,0.0009608123,0.0009285781,0.0009830939,0.0003760525,0.0008616208,0.001164191,0.00160971,0.001115533],"category_scores_gemma":[0.001849074,0.0004712907,0.000661828,0.001005093,0.0007811785,0.0009018033,0.0006655076,0.0007843011,0.0001598833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009917553,"about_ca_system_score_gemma":0.001290463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004544623,"about_ca_topic_score_gemma":0.003488649,"domain_scores_codex":[0.9995925,0.0001900897,0.00001301747,0.00007175322,0.00008613918,0.00004649423],"domain_scores_gemma":[0.9994897,0.0003228795,0.00006610873,0.00002781386,0.00007093934,0.00002257833],"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":[0.00001607261,0.00002666614,0.0002127538,0.00001146912,0.00002663945,0.00002314557,0.00002589915,0.9786925,0.0007130483,0.004052375,0.0001409665,0.01605841],"study_design_scores_gemma":[0.00001109882,0.0000167375,0.00003272633,0.00000300486,0.000008005192,0.000006880995,0.000006425614,0.9974589,0.0001585123,0.002139109,0.0001561256,0.000002559059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03328956,0.0001816456,0.9640076,0.0002311799,0.00002211564,0.00005790621,0.0000172834,0.0001972783,0.001995496],"genre_scores_gemma":[0.524825,0.0003881896,0.4718403,0.000155007,0.0000430629,0.0002594822,0.00008624568,0.00006861275,0.002334093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004544623,"threshold_uncertainty_score":0.009036303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03453306002744725,"score_gpt":0.2589592298276795,"score_spread":0.2244261698002323,"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."}}