{"id":"W2317802191","doi":"10.1109/tem.2016.2527684","title":"A Discrete Stress–Strength Interference Theory-Based Dynamic Supplier Selection Model for Maintenance Service Outsourcing","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Engineering Management","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada; National Natural Science Foundation of China","keywords":"Outsourcing; Service (business); Asset specificity; Operations research; Business; Computer science; Supply chain; Reliability (semiconductor); Process management; Reliability engineering; Industrial organization; Marketing; Engineering; Transaction cost; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002718696,0.001422102,0.001983301,0.001467991,0.0007639887,0.002254537,0.003628837,0.002109244,0.006800955],"category_scores_gemma":[0.005172499,0.0008829604,0.00177875,0.001733301,0.001330747,0.001909082,0.001627575,0.002057547,0.000850451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003115839,"about_ca_system_score_gemma":0.00196694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01530423,"about_ca_topic_score_gemma":0.009057083,"domain_scores_codex":[0.9976624,0.0007726969,0.0001376134,0.0005028502,0.0006001024,0.0003243477],"domain_scores_gemma":[0.9971349,0.001672737,0.0004088907,0.00008025019,0.0005521902,0.0001510541],"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":[0.00006427147,0.000060109,0.001099479,0.00009149013,0.00007894994,0.0003014414,0.0001486923,0.9617867,0.000685072,0.02679426,0.0008777208,0.008011763],"study_design_scores_gemma":[0.00001124117,0.00002424841,0.0001839807,0.000006689886,0.00001871148,0.00002662349,0.00001892126,0.9947055,0.00005293456,0.004643737,0.000296268,0.00001112129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02846033,0.000702123,0.9580795,0.0009267317,0.00009567718,0.0001765784,0.0003325808,0.000207991,0.0110184],"genre_scores_gemma":[0.9326783,0.001203164,0.05251035,0.0002501078,0.0001183738,0.0005792846,0.0004029587,0.00005930623,0.01219807],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01530423,"threshold_uncertainty_score":0.03043032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005278831472840508,"score_gpt":0.1919072550341095,"score_spread":0.186628423561269,"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."}}