{"id":"W2025721140","doi":"10.1108/17410380610688250","title":"Cellular manufacturing versus a hybrid system: a comparative study","year":2006,"lang":"en","type":"article","venue":"Journal of Manufacturing Technology Management","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Cellular manufacturing; Job shop; Schedule; Scheduling (production processes); Flexible manufacturing system; Computer science; Manufacturing engineering; Manufacturing; Originality; Industrial engineering; Job shop scheduling; Reliability engineering; Engineering; Operations management; Flow shop scheduling; Business","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":[0.001981146,0.0004179286,0.0005442151,0.00107011,0.0003199613,0.001369313,0.0005092759,0.0004604913,0.00385466],"category_scores_gemma":[0.003706167,0.0001438944,0.0005137613,0.001171836,0.0003792099,0.0009037163,0.0006824444,0.0002451282,0.0003429881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222076,"about_ca_system_score_gemma":0.0004525026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003068627,"about_ca_topic_score_gemma":0.00314228,"domain_scores_codex":[0.9985398,0.0007244574,0.0000667927,0.0001270986,0.0003880545,0.0001538337],"domain_scores_gemma":[0.9956996,0.002729176,0.0002891126,0.0002879078,0.000793294,0.0002009024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.014497,0.002110225,0.08506815,0.00280045,0.001494566,0.001102141,0.0006960189,0.4967812,0.02830644,0.007427639,0.002483406,0.3572328],"study_design_scores_gemma":[0.0009766844,0.07913952,0.1517581,0.0002413405,0.002270491,0.001273125,0.00391699,0.7114818,0.03163212,0.003525944,0.01353241,0.0002515104],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985204,0.001139182,0.006312837,0.00006975004,0.0000530732,0.0001320828,0.0001219205,0.00005132829,0.006915848],"genre_scores_gemma":[0.9974416,0.0002022929,0.00180651,0.00001223471,0.00001261185,0.00001848442,0.00007831285,0.000004285327,0.0004234948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00385466,"threshold_uncertainty_score":0.01289511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01249678816978784,"score_gpt":0.2249362543725474,"score_spread":0.2124394662027596,"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."}}