{"id":"W1978542154","doi":"10.1109/ptc.2005.4524593","title":"A probabilistic approach to life cycle management","year":2005,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kinectrics (Canada)","funders":"Uniwersytet Łódzki","keywords":"Probabilistic logic; Computer science; Monte Carlo method; Continuation; Reliability engineering; Product life-cycle management; Component (thermodynamics); Simple (philosophy); Process (computing); Production (economics); Operations research; Exponential function; Work (physics); Mathematical optimization; Industrial engineering; Engineering; Mathematics; Artificial intelligence; Statistics; Economics","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":[0.00006495259,0.00006214212,0.00005970743,0.00003332126,0.00001692951,0.00001886842,0.00006901145,0.00002186729,0.00006291216],"category_scores_gemma":[0.00001213317,0.00005513874,0.0000181611,0.0001176826,0.000006612718,0.00006815769,0.00001861131,0.00003139845,0.0001950811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005197553,"about_ca_system_score_gemma":0.00000229269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002113186,"about_ca_topic_score_gemma":0.000003002266,"domain_scores_codex":[0.9995853,0.000003776134,0.0001007911,0.0001088949,0.00006514938,0.0001361268],"domain_scores_gemma":[0.9997499,0.000004492898,0.000003667806,0.0001543053,0.00001295476,0.00007470868],"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":[0.00000172605,0.00003117503,0.000002647346,0.00005451577,0.000006870727,8.732319e-8,0.00008138569,0.9654131,0.000005323554,0.01809868,0.005077043,0.01122742],"study_design_scores_gemma":[0.0001129931,0.000007311595,0.0002349856,0.000005971982,0.000005432732,5.384873e-7,0.00005732074,0.9687796,0.00003156009,0.0004540042,0.03020966,0.000100658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005915423,0.00002355522,0.461154,0.0002749443,0.0000554317,0.0003674775,5.885595e-7,0.000362847,0.5318457],"genre_scores_gemma":[0.830351,0.00002342839,0.1673114,0.0003378741,0.00005251846,0.00009977285,0.000003725108,0.00001428289,0.001805999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8244356,"threshold_uncertainty_score":0.2507437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006375206120143131,"score_gpt":0.1835159908283109,"score_spread":0.1771407847081678,"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."}}