{"id":"W2386166483","doi":"","title":"Application of expert system in distinguishing the fault type and the fault location on the transmission lines of power distribution system","year":2001,"lang":"en","type":"article","venue":"Relay","topic":"Power Systems and Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Fault (geology); Fault indicator; Interpolation (computer graphics); Stuck-at fault; Point (geometry); Line (geometry); Fault model; Transmission line; Electric power transmission; Computer science; Engineering; Real-time computing; Fault detection and isolation; Artificial intelligence; Mathematics; Electrical engineering; Telecommunications","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":[0.0004759287,0.00008482053,0.0001455923,0.00002014386,0.00005425586,0.0000150406,0.00016716,0.00008809215,3.959405e-7],"category_scores_gemma":[0.0001034492,0.00003866748,0.00002400872,0.0003215109,0.00005869212,0.00003222419,0.00001488162,0.0001181098,0.000001491479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006305532,"about_ca_system_score_gemma":0.000005685682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001925281,"about_ca_topic_score_gemma":0.000009079996,"domain_scores_codex":[0.9993568,0.00005524098,0.000274964,0.00008930279,0.0001365569,0.00008713359],"domain_scores_gemma":[0.9993725,0.0001810769,0.00009074288,0.0002698647,0.00007670643,0.000009066441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007189245,0.0002114321,0.007035133,0.005591864,0.0003572439,0.00001271155,0.0314793,0.2069542,0.04291631,0.5732295,0.002332135,0.1291613],"study_design_scores_gemma":[0.001132722,0.00008156908,0.006931875,0.003157151,0.00004489949,0.00005074748,0.01880522,0.9231654,0.01430549,0.0001058211,0.03194415,0.0002749014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8585809,0.006525577,0.1300734,0.0007683702,0.0003197758,0.001038868,0.00001186082,0.0003261571,0.00235509],"genre_scores_gemma":[0.9997585,0.0001219506,0.00001649647,0.000002710005,0.00002387917,0.0000503244,0.000005946882,0.000009113863,0.0000110308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7162113,"threshold_uncertainty_score":0.1576814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007461682296984948,"score_gpt":0.2109891619840246,"score_spread":0.2035274796870396,"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."}}