{"id":"W3202578034","doi":"10.18280/i2m.200404","title":"Machine Learning MOSA Monitoring System","year":2021,"lang":"en","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"High voltage insulation and dielectric phenomena","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lightning arrester; Surge arrester; Engineering; Voltage; Reliability engineering; Computer science; Electrical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004120717,0.0004733958,0.0005530598,0.0006641634,0.00023752,0.0006242212,0.0005819968,0.000614385,0.003074253],"category_scores_gemma":[0.000968738,0.000142393,0.0002470451,0.0004018199,0.000140463,0.0006313205,0.0003373787,0.0003644248,0.001579265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003009978,"about_ca_system_score_gemma":0.0003654874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000835794,"about_ca_topic_score_gemma":0.0005708683,"domain_scores_codex":[0.999678,0.00004515813,0.00002255077,0.0001215084,0.0001029251,0.00002983637],"domain_scores_gemma":[0.9995908,0.00008892069,0.00006375976,0.0000500564,0.0001903669,0.00001606058],"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":[0.0006983035,0.0002709018,0.01144702,0.000250435,0.00008589513,0.0003472225,0.00009116115,0.09020879,0.07287575,0.00367215,0.009579011,0.8104734],"study_design_scores_gemma":[0.00003773318,0.0003241824,0.00597237,0.00001918686,0.0000354557,0.0003099787,0.00003186301,0.9484585,0.0344708,0.002004976,0.008305019,0.00002992294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08321002,0.0004768668,0.8964274,0.0003754516,0.0001710162,0.0001964096,0.0006491991,0.01034031,0.008153339],"genre_scores_gemma":[0.8841228,0.0003383785,0.1059021,0.0002377482,0.0001126955,0.0002207662,0.001189552,0.00007368504,0.007802236],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003074253,"threshold_uncertainty_score":0.01028442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02420187325360357,"score_gpt":0.27278222191204,"score_spread":0.2485803486584364,"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."}}