{"id":"W2023857282","doi":"10.1007/s10845-008-0126-0","title":"A virtual collaborative maintenance architecture for manufacturing enterprises","year":2008,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Architecture; Engineering; Reliability (semiconductor); Production (economics); Enterprise architecture; Systems engineering; Enterprise architecture management; Manufacturing engineering; Reliability engineering; Computer science","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":[0.002389055,0.0003606311,0.0004619378,0.0007919321,0.001481408,0.003312009,0.002752399,0.001908107,0.003340979],"category_scores_gemma":[0.002478164,0.0004725298,0.0006100737,0.0006631482,0.000758614,0.004285419,0.003846156,0.0009188399,0.0006790788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008761733,"about_ca_system_score_gemma":0.001760639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004186337,"about_ca_topic_score_gemma":0.004301608,"domain_scores_codex":[0.9989679,0.0003070576,0.00009764177,0.0001930948,0.0002869165,0.0001474937],"domain_scores_gemma":[0.9979218,0.0003095608,0.0001293075,0.0009046377,0.0003713729,0.0003633868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001437011,0.001164232,0.006762866,0.0002091995,0.0002171738,0.0008260391,0.002405352,0.3426387,0.03178479,0.1629839,0.01252776,0.4370431],"study_design_scores_gemma":[0.0001000808,0.0002971106,0.001112398,0.00003523939,0.000111336,0.000276283,0.0003212536,0.9213535,0.007636372,0.04418886,0.02451258,0.0000550034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1112965,0.0003108905,0.8721532,0.0007765057,0.0001069749,0.0001640826,0.0000707381,0.004460788,0.01066041],"genre_scores_gemma":[0.7283521,0.0001665168,0.265622,0.0001112109,0.00004240635,0.0001241308,0.0001749593,0.0001340424,0.005272536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004186337,"threshold_uncertainty_score":0.01263469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009793697706679167,"score_gpt":0.2155327108321344,"score_spread":0.2057390131254552,"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."}}