{"id":"W137660314","doi":"","title":"A Mobile Agent System for University Course Timetabling.","year":2005,"lang":"en","type":"article","venue":"","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Negotiation; Mobile agent; Course (navigation); Class (philosophy); Scheduling (production processes); Autonomy; Distributed computing; Set (abstract data type); Multi-agent system; Operations research; Artificial intelligence; Operations management; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003365114,0.0001135263,0.0001309973,0.00007692396,0.0001333968,0.00007511521,0.0008030665,0.00003146112,0.00005221119],"category_scores_gemma":[0.000002033526,0.0001101173,0.00009650765,0.0002865908,0.00001545528,0.0002861466,0.0002702129,0.00004167754,0.0002950059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002621207,"about_ca_system_score_gemma":0.00005416051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001850224,"about_ca_topic_score_gemma":0.00001702096,"domain_scores_codex":[0.9989635,0.00004159609,0.0001384251,0.0003727656,0.000187618,0.00029613],"domain_scores_gemma":[0.9990994,0.00005141303,0.0000667121,0.0006118487,0.00006109163,0.0001095068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002514815,0.0002961942,0.00005002543,0.0001055951,0.000132472,0.00005046121,0.0002434167,0.04303299,0.00007821281,0.3529509,0.1635903,0.4394443],"study_design_scores_gemma":[0.0004892938,0.00008362793,0.00002896639,0.00001023033,0.00002285532,0.000002936323,0.00009905297,0.4044821,0.0003331323,0.00001748156,0.5943025,0.0001278333],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001250112,0.0001641415,0.9833826,0.0002438009,0.0002813509,0.0008511711,0.000003152977,0.0004609951,0.01336271],"genre_scores_gemma":[0.6914487,0.00002304767,0.2846685,0.0005047954,0.0002091947,0.00006275836,0.00000557181,0.00001332962,0.02306407],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.698714,"threshold_uncertainty_score":0.4490453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213280867979599,"score_gpt":0.2198235601030668,"score_spread":0.2076907514232708,"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."}}