{"id":"W137723978","doi":"10.1023/a:1026321126865","title":"Supervisory Control of Functionally-Expandable Manufacturing Systems","year":2003,"lang":"en","type":"article","venue":"International Journal of Flexible Manufacturing Systems","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Consejo Nacional de Ciencia y Tecnología","keywords":"Supervisor; Workcell; Supervisory control; A priori and a posteriori; Set (abstract data type); Production (economics); Control (management); Engineering; Computer science; Control engineering; Artificial intelligence; Robot; Management; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007174187,0.0003320515,0.0005909171,0.000629727,0.00007296208,0.0002282813,0.0005677703,0.0001636452,0.0002021794],"category_scores_gemma":[0.00004472242,0.0003006511,0.0002308371,0.00006981332,0.00004120729,0.0005938284,0.00002666836,0.0003474752,0.00002013106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002623639,"about_ca_system_score_gemma":0.00007638262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007091993,"about_ca_topic_score_gemma":0.000001298201,"domain_scores_codex":[0.9970219,0.00009575976,0.001310761,0.0002134246,0.001006224,0.0003519175],"domain_scores_gemma":[0.9983952,0.0001628823,0.0005867865,0.000249114,0.0004469879,0.0001590039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008524507,0.00005852854,0.0005272462,0.0003889197,0.0007193573,0.00003978581,0.0001713987,0.9946482,0.0005588943,0.001426569,0.0005182701,0.0008575953],"study_design_scores_gemma":[0.009245669,0.0004478916,0.00788337,0.002665219,0.0003920577,0.002621099,0.002245759,0.04708997,0.7491899,0.0007218719,0.1756878,0.001809322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5825544,0.009404114,0.3686231,0.00006004984,0.02388596,0.000549554,0.00007817692,0.0002860214,0.01455861],"genre_scores_gemma":[0.9975317,0.0002372107,0.0003361931,0.00001883994,0.0006076885,0.00001909814,0.000008866205,0.00006446514,0.001175996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9475582,"threshold_uncertainty_score":0.9999446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01481076153076084,"score_gpt":0.2129025225763812,"score_spread":0.1980917610456204,"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."}}