{"id":"W3101680449","doi":"10.36001/phmconf.2020.v12i1.1155","title":"Noisy Multipath Parallel Hybrid Model for Remaining Useful Life Estimation (NMPM)","year":2020,"lang":"en","type":"article","venue":"Annual Conference of the PHM Society","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Robustness (evolution); Convolutional neural network; Artificial neural network; Artificial intelligence; Deep learning; Multipath propagation; Pattern recognition (psychology); Perceptron; Algorithm; Channel (broadcasting)","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":[0.0001770583,0.0001826905,0.000252713,0.00001025241,0.0000831741,0.00003355149,0.000426042,0.00007921236,0.000009653675],"category_scores_gemma":[0.0003834821,0.000154233,0.0002536005,0.00008774066,0.00005893179,0.0002356228,0.0001108175,0.0002097663,0.000003182231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003055546,"about_ca_system_score_gemma":0.0000662951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001608551,"about_ca_topic_score_gemma":0.000003193902,"domain_scores_codex":[0.9990812,0.00002032559,0.0002887929,0.0001969679,0.0001880738,0.0002246652],"domain_scores_gemma":[0.9992557,0.0001122702,0.00009502507,0.0002597723,0.0001787669,0.00009850709],"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":[0.00003259954,0.00007391004,0.001261632,0.0006089662,0.0001845233,4.96636e-7,0.03281689,0.8270432,0.005176835,0.002118652,0.1263652,0.004317032],"study_design_scores_gemma":[0.00028683,0.00003612009,0.0003765192,0.00005499175,0.00003081105,4.993517e-7,0.0003347963,0.9919075,0.005225419,0.001248552,0.00032287,0.000175091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2052511,0.00005760886,0.7906035,0.002324767,0.00007137177,0.0005872672,0.0002993838,0.0005023895,0.0003026976],"genre_scores_gemma":[0.9211144,0.00005153471,0.07794259,0.000664533,0.00005299177,0.00009683527,0.00002235219,0.00003343878,0.00002127108],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7158633,"threshold_uncertainty_score":0.6289439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04951003551731543,"score_gpt":0.2812955657095663,"score_spread":0.2317855301922509,"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."}}