{"id":"W317510280","doi":"10.1016/j.ress.2015.04.013","title":"Search for all d-MPs for all d levels in multistate two-terminal networks","year":2015,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":79,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Path (computing); Binary number; Heuristic; Reliability (semiconductor); Algorithm; Binary search algorithm; Value (mathematics); Mathematics; Integer (computer science); Computer science; Mathematical optimization; Search algorithm; Statistics; Arithmetic; Power (physics); Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002690276,0.0003831543,0.0006003389,0.0001375529,0.00004476282,0.000059997,0.0002924546,0.0002445647,0.000002490197],"category_scores_gemma":[0.0003147514,0.0003981253,0.0001926962,0.0002499363,0.00003450279,0.0002720446,0.00004055188,0.0003012627,0.000007228233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001379612,"about_ca_system_score_gemma":0.00006655222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001037303,"about_ca_topic_score_gemma":0.00003099449,"domain_scores_codex":[0.9973771,0.00006409565,0.0009132911,0.0005298244,0.0002438795,0.000871826],"domain_scores_gemma":[0.9982851,0.000490391,0.00005711941,0.0005983681,0.0002882483,0.0002807592],"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":[0.0001309174,0.0000334824,0.0003064413,0.001754957,0.00003665371,0.000003959966,0.0003975206,0.9950519,0.0002020044,0.0009419349,0.0002080468,0.0009321572],"study_design_scores_gemma":[0.002096642,0.00009300604,0.0008061667,0.0002833355,0.00002984212,0.00001603905,0.0001212864,0.9886588,0.0003302496,0.00003775974,0.007105926,0.0004209752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04412477,0.0002156377,0.9505675,0.0001072729,0.00134232,0.00258279,0.0001626825,0.0007004855,0.0001964862],"genre_scores_gemma":[0.9625528,0.00003144016,0.03627667,0.00001576008,0.0002567501,0.0005634499,0.0001350931,0.0001149572,0.00005305234],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9184281,"threshold_uncertainty_score":0.9998471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387257834581962,"score_gpt":0.2593243840548468,"score_spread":0.2354518057090272,"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."}}