{"id":"W2115910105","doi":"10.1109/pes.2006.1709589","title":"Topological observability analysis using heuristic rule based expert system","year":2006,"lang":"en","type":"article","venue":"2006 IEEE Power Engineering Society General Meeting","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hatch (Canada)","funders":"","keywords":"Observability; Heuristic; Spanning tree; Observable; Minimum spanning tree; Computer science; Graph; Electric power system; Graph theory; Expert system; Tree (set theory); Mathematics; Mathematical optimization; Topology (electrical circuits); Algorithm; Theoretical computer science; Power (physics); Discrete mathematics; Artificial intelligence; Combinatorics; Applied mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001702085,0.0005692363,0.0007570739,0.001206325,0.000328925,0.001142299,0.0008522426,0.0005983622,0.001986681],"category_scores_gemma":[0.01152036,0.0002520022,0.0005161269,0.0004602008,0.0006441266,0.001024297,0.000555047,0.0006877187,0.0002240266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007072735,"about_ca_system_score_gemma":0.000845102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003365223,"about_ca_topic_score_gemma":0.002464344,"domain_scores_codex":[0.9984685,0.0005566048,0.0001002531,0.0002551695,0.0005306996,0.00008878105],"domain_scores_gemma":[0.9932107,0.00485782,0.000470911,0.0004602376,0.0009157492,0.00008460807],"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":[0.0001046939,0.00008718178,0.00184516,0.000126173,0.00008963812,0.0002477333,0.0002404344,0.8452851,0.004566291,0.0174518,0.0007416601,0.1292142],"study_design_scores_gemma":[0.000009464884,0.00002173365,0.0002152807,0.000007383874,0.00001111903,0.00002300341,0.00002558243,0.9898057,0.0009631297,0.008573351,0.0003372947,0.000006967509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0175559,0.00002369529,0.9806845,0.00004352291,0.000005520693,0.00005093267,0.00005203941,0.0003944277,0.001189457],"genre_scores_gemma":[0.6125956,0.00007777518,0.3859237,0.00005225624,0.00001706086,0.0001920711,0.0002921554,0.00004163498,0.00080774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003365223,"threshold_uncertainty_score":0.009001613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01098997573597128,"score_gpt":0.2154739357472287,"score_spread":0.2044839600112574,"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."}}