{"id":"W2789750499","doi":"10.1109/tr.2017.2781147","title":"An Integrated Prognostics Method for Failure Time Prediction of Gears Subject to the Surface Wear Failure Mode","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Reliability","topic":"Gear and Bearing Dynamics Analysis","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Prognostics; Failure mode and effects analysis; Structural engineering; Engineering; Mode (computer interface); Tool wear; Reliability engineering; Mechanical engineering; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0005714825,0.0001648267,0.000220307,0.00008408762,0.0001415197,0.00003243592,0.0002027295,0.0001202346,0.00004226291],"category_scores_gemma":[0.00003020914,0.0001279031,0.0001615379,0.0004985427,0.00006113906,0.00008273838,8.562847e-7,0.0002430134,0.00002518938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008882293,"about_ca_system_score_gemma":0.00003306772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002475344,"about_ca_topic_score_gemma":0.0008586755,"domain_scores_codex":[0.998951,0.00009186366,0.0002798853,0.0002781113,0.000187312,0.0002117896],"domain_scores_gemma":[0.9988559,0.0001674611,0.00002958547,0.0005791242,0.000282567,0.00008539528],"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":[0.00004606491,0.0001075951,0.00005485373,0.00003916288,0.00008764207,8.747128e-8,0.0003933073,0.9644297,0.03197189,0.000007383539,0.0002856704,0.002576598],"study_design_scores_gemma":[0.0001477823,0.0003274409,0.0003625435,0.00001885956,0.000149618,0.000001239615,0.000119637,0.9599395,0.03786271,0.00007159642,0.0008862963,0.0001127337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2917332,0.000001641922,0.7068541,0.0001972166,0.0001540525,0.0004209989,0.0004523832,0.000163742,0.00002265283],"genre_scores_gemma":[0.9226633,0.000002755391,0.07712389,0.00001282166,0.00003508994,0.00003888066,0.0000185416,0.00002645855,0.00007823951],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6309301,"threshold_uncertainty_score":0.5215739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007420846027828608,"score_gpt":0.243594035063229,"score_spread":0.2361731890354004,"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."}}