{"id":"W1519234219","doi":"10.3963/jmpm.v1i2.32","title":"Effectiveness of SLA Project with Spare Parts Management: The case of a telecom equipment industry","year":2013,"lang":"en","type":"article","venue":"Journal of Modern Project Management","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Spare part; Business; Telecommunications equipment; Operations management; Portfolio; Enhanced Telecom Operations Map; Project portfolio management; Process management; Telecommunications; Service (business); Computer science; Operations research; Project management; Marketing; Service provider; Engineering; Systems engineering; Finance","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":[0.006019732,0.0003788554,0.0004823331,0.001911156,0.002122956,0.002789124,0.0010802,0.002207379,0.007435636],"category_scores_gemma":[0.0158848,0.0002220254,0.0004608332,0.001295915,0.001605015,0.002813546,0.001741157,0.001027505,0.0004316873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00267631,"about_ca_system_score_gemma":0.002208843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01326879,"about_ca_topic_score_gemma":0.009661365,"domain_scores_codex":[0.9971235,0.001778327,0.0001008844,0.0001637997,0.0003378067,0.0004955866],"domain_scores_gemma":[0.9866245,0.008968191,0.001043019,0.0005618237,0.00142906,0.001373461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.003583719,0.00512379,0.1667121,0.0005967009,0.0002281751,0.01183848,0.007937081,0.5510515,0.006419164,0.1088202,0.004669945,0.1330191],"study_design_scores_gemma":[0.0002969378,0.002381974,0.06929605,0.0001445583,0.0001414304,0.001036772,0.02355504,0.863465,0.003422727,0.03060182,0.005566522,0.00009113928],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9763712,0.0001618533,0.005304103,0.0007238998,0.00001164918,0.0001092385,0.00005411402,0.00002823183,0.01723572],"genre_scores_gemma":[0.9971445,0.00005097113,0.001861366,0.00001268421,0.000006177711,0.00001727066,0.00002182333,0.000005778648,0.0008793884],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01326879,"threshold_uncertainty_score":0.03183573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05532109936773852,"score_gpt":0.2950604151787267,"score_spread":0.2397393158109882,"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."}}