{"id":"W4310228487","doi":"10.21203/rs.3.rs-2310302/v1","title":"Anomaly Detection in Three-Axis CNC Machines using LSTM Networks and Transfer Learning","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Anomaly detection; Anomaly (physics); Transfer (computing); Transfer of learning; Artificial intelligence; Computer science; Physics; Parallel computing","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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001689403,0.0002183777,0.0002616335,0.0006966706,0.0007882747,0.0003804407,0.0007734451,0.0002628847,0.00008473467],"category_scores_gemma":[0.00004647852,0.0002339777,0.0001090822,0.001159455,0.000100439,0.0002048474,0.001832271,0.002975505,0.00000300944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003176245,"about_ca_system_score_gemma":0.0001292789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002846037,"about_ca_topic_score_gemma":0.000803691,"domain_scores_codex":[0.9971622,0.000527539,0.0003301476,0.0008887664,0.0005818732,0.0005095187],"domain_scores_gemma":[0.9988254,0.0001894633,0.00005459281,0.000657526,0.0001552243,0.0001177399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008803722,0.0002890009,0.05431687,0.0007107565,0.00006919964,0.00008849538,0.001359034,0.2790559,0.003114819,0.01139864,0.00004314472,0.6494661],"study_design_scores_gemma":[0.0001358773,0.0001790388,0.02099284,0.0001014842,0.000004053841,0.00001851914,0.00007946687,0.9713124,0.0003643401,0.004812048,0.001733011,0.0002669448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3120167,0.000674291,0.6857787,0.0001743517,0.00007793384,0.0007168871,0.000004460192,0.0002450852,0.0003115972],"genre_scores_gemma":[0.9947402,0.0004001939,0.004020773,0.00001396828,0.000112989,0.0005463434,0.00001004929,0.00003083737,0.0001246826],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6922565,"threshold_uncertainty_score":0.9993247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05767111220020908,"score_gpt":0.3656947336235243,"score_spread":0.3080236214233152,"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."}}