{"id":"W4409787760","doi":"10.61091/jcmcc127a-512","title":"Simulated annealing algorithm-based scheduling optimization of lean manufacturing line and evaluation of the calibration effect of electrical measuring instruments","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Simulated annealing; Calibration; Computer science; Scheduling (production processes); Lean manufacturing; Algorithm; Industrial engineering; Manufacturing engineering; Engineering; Mathematics; Operations management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001021743,0.0005744474,0.0008194061,0.0005230216,0.0003673729,0.0006204001,0.0006470143,0.000729315,0.001257231],"category_scores_gemma":[0.001872221,0.0004161885,0.0006343703,0.0005083726,0.0004198074,0.0004722556,0.0003081726,0.0004824267,0.0001075249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041416,"about_ca_system_score_gemma":0.001392448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008085989,"about_ca_topic_score_gemma":0.005111944,"domain_scores_codex":[0.9996019,0.0002003229,0.00001074062,0.00005202524,0.00007958188,0.00005547472],"domain_scores_gemma":[0.9987205,0.000862395,0.0001113454,0.0000606344,0.0002064585,0.00003865196],"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":[0.00007568906,0.00003284158,0.0002500276,0.00001606295,0.00001135289,0.000008450632,0.00001053328,0.9941591,0.001303166,0.0005633524,0.00006104448,0.003508406],"study_design_scores_gemma":[0.000005271867,0.00003017571,0.0001241925,0.000001012727,0.000003987711,0.000001233376,0.000002756349,0.9992163,0.0004798946,0.0001001571,0.00003370125,0.000001303789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5394031,0.0004677312,0.4513761,0.0002106107,0.00006968747,0.00009982772,0.000072617,0.0005059754,0.007794372],"genre_scores_gemma":[0.9676012,0.00005548872,0.03156128,0.0000156663,0.000004049589,0.00003037887,0.00003485513,0.00002567587,0.000671473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008085989,"threshold_uncertainty_score":0.01607788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01060779014921749,"score_gpt":0.2420959068308305,"score_spread":0.231488116681613,"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."}}