{"id":"W2001883003","doi":"10.1115/imece2003-42802","title":"A Sensor-Driven Approach to Distributed Shop Floor Planning and Control","year":2003,"lang":"en","type":"article","venue":"","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Flexibility (engineering); Architecture; Scheduling (production processes); Dynamism; Process (computing); Adaptability; Real-time computing; Distributed computing; Control (management); Software engineering; Systems engineering; Engineering; Artificial intelligence; Operating system","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":[0.0008260014,0.0005592995,0.0005766999,0.0003675245,0.0004998058,0.001319356,0.001745913,0.0006889297,0.001723242],"category_scores_gemma":[0.001012132,0.0004609933,0.0006096466,0.0004992818,0.0009092327,0.001198067,0.00071256,0.001141887,0.0003261508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000882465,"about_ca_system_score_gemma":0.001449653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001847876,"about_ca_topic_score_gemma":0.002788363,"domain_scores_codex":[0.9993671,0.0001401475,0.00002863747,0.0001316874,0.0002817657,0.00005081555],"domain_scores_gemma":[0.9996431,0.0001626536,0.00002954395,0.00006431556,0.00007501617,0.0000253114],"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":[0.00008025044,0.0001122286,0.0003598146,0.0001812007,0.0000597809,0.0001354532,0.0001723434,0.7273141,0.01423904,0.1715137,0.001499071,0.08433314],"study_design_scores_gemma":[0.00002216984,0.00005061773,0.0001102147,0.00001333254,0.00001658059,0.00003683052,0.00002653304,0.9384201,0.004969945,0.04882273,0.00749793,0.00001295685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00200657,0.00006890623,0.9961904,0.00007322225,0.00001771857,0.00002871212,0.00001686108,0.0002241926,0.001373412],"genre_scores_gemma":[0.3174079,0.000381096,0.6775972,0.0001213073,0.00006416412,0.0002609309,0.0001306217,0.0001188039,0.003917904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001847876,"threshold_uncertainty_score":0.006402731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01253273059151257,"score_gpt":0.2137449803775017,"score_spread":0.2012122497859891,"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."}}