{"id":"W2385852617","doi":"","title":"Discussion on Compensation Mode for Power Distribution Network","year":2001,"lang":"en","type":"article","venue":"Dianli zidonghua shebei","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Arc suppression; Compensation (psychology); Ground; Mode (computer interface); Electromagnetic coil; Power (physics); Point (geometry); Arc (geometry); Control theory (sociology); Electrical engineering; Computer science; Electric power system; Electronic engineering; Engineering; Mathematics; Physics; Psychology; Mechanical engineering; Control (management); Artificial intelligence","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":[0.00008051575,0.0001822789,0.0002068642,0.0000287388,0.000129261,0.00003554983,0.00009227865,0.0001002335,0.00002645115],"category_scores_gemma":[0.00002409252,0.0001371,0.0001035147,0.0001379834,0.00001509845,0.0001386897,0.000008161493,0.0001062245,0.00007214438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001202424,"about_ca_system_score_gemma":0.000004881806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008527905,"about_ca_topic_score_gemma":0.00003007495,"domain_scores_codex":[0.9990234,0.00002140144,0.0002324854,0.0001987903,0.0001504529,0.0003734881],"domain_scores_gemma":[0.9995206,0.00006622227,0.00003643332,0.0002446724,0.00003822558,0.00009386148],"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":[0.0002425894,0.00007003218,0.002241862,0.00004475657,0.00006676021,0.000009524219,0.0002319361,0.9241375,0.003093956,0.01129713,0.02331177,0.03525223],"study_design_scores_gemma":[0.002279721,0.000235485,0.01572262,0.000172018,0.00004305257,0.00001148073,0.0001548635,0.608944,0.0005874315,0.005394987,0.3656727,0.0007816596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1427615,0.0003922753,0.842105,0.000631896,0.002651664,0.001158787,0.0002397311,0.000858629,0.009200496],"genre_scores_gemma":[0.9982244,0.00003160128,0.00018097,0.00008157679,0.0005130288,0.00007214212,0.0004338819,0.000042147,0.0004202029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.855463,"threshold_uncertainty_score":0.5590776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008302169873546324,"score_gpt":0.2311040424017995,"score_spread":0.2228018725282531,"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."}}