{"id":"W4318562013","doi":"10.1016/j.ress.2023.109130","title":"A comparison study of centralized and decentralized federated learning approaches utilizing the transformer architecture for estimating remaining useful life","year":2023,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":70,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Prognostics; Transformer; Raw data; Architecture; Computer science; Asset management; Federated learning; Data mining; Reliability engineering; Distributed computing; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002901947,0.0002720893,0.0005693097,0.00004858916,0.0005654684,0.00006254835,0.0001876089,0.00009812205,0.000005159738],"category_scores_gemma":[0.0009682096,0.0002098443,0.0001098466,0.0005039594,0.00007560111,0.00009302006,0.00006777753,0.0003546524,0.000003125542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001795678,"about_ca_system_score_gemma":0.00001506572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002352758,"about_ca_topic_score_gemma":0.00001688584,"domain_scores_codex":[0.997454,0.0002745879,0.0008733802,0.0004759018,0.0003806928,0.0005413909],"domain_scores_gemma":[0.9982944,0.001073368,0.0002104529,0.0002606547,0.00001951515,0.0001416665],"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":[0.0001121804,0.00005660344,0.07603657,0.0006800362,0.00005040736,6.859937e-7,0.01279457,0.9060678,0.0005926701,0.00003493154,0.000007375328,0.003566113],"study_design_scores_gemma":[0.001043286,0.0001429656,0.04047639,0.0002759578,0.00006419948,0.000004953411,0.01798373,0.9392619,0.0001908595,0.000004899154,0.0003247515,0.0002260764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9062707,0.0000389425,0.09152085,0.00012234,0.0002244951,0.001309232,0.000006313548,0.0004238292,0.00008325507],"genre_scores_gemma":[0.9914712,0.000002967477,0.008309336,0.000002199651,0.0000546708,0.0000962657,0.00001084871,0.00004189194,0.00001058459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08520049,"threshold_uncertainty_score":0.8557203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05113267390719354,"score_gpt":0.2729952128577262,"score_spread":0.2218625389505327,"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."}}