{"id":"W2106824791","doi":"10.1109/tpwrs.2009.2030358","title":"Disco Operation Considering DG Units and Their Goodness Factors","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"King Abdulaziz City for Science and Technology","keywords":"Goodness of fit; Distributed generation; AC power; Scheduling (production processes); Power system simulation; Reliability engineering; Computation; Electric power system; Power factor; Mathematical optimization; Engineering; Power (physics); Computer science; Voltage; Mathematics; Electrical engineering; Renewable energy; Algorithm","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":[0.00008290627,0.0002409884,0.0002180344,0.0001088379,0.0001519778,0.0001435646,0.00007326757,0.0001154065,0.00002372741],"category_scores_gemma":[0.000002884751,0.0002119319,0.00004195864,0.0002166047,0.00002722106,0.000354407,4.439823e-7,0.0002031716,0.00003038202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001096839,"about_ca_system_score_gemma":0.00001695248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002619894,"about_ca_topic_score_gemma":0.00001262142,"domain_scores_codex":[0.9991447,0.00003634003,0.0002586476,0.0002030665,0.0001195191,0.0002376971],"domain_scores_gemma":[0.999554,0.00004539756,0.00002416179,0.0002182442,0.00005024635,0.000107888],"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":[0.00003990119,0.0001687551,0.0001111858,0.0001470533,0.0002118129,0.00001190599,0.004984051,0.9210148,0.06973239,0.0006976576,0.0008507078,0.002029781],"study_design_scores_gemma":[0.00348625,0.001657247,0.005040925,0.001025522,0.0001979293,0.0002434716,0.01471543,0.4928923,0.458579,0.00008413495,0.01866842,0.003409354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3539908,0.0001659913,0.6423162,0.00003099554,0.002019897,0.0002469709,0.0001412307,0.000364678,0.0007232511],"genre_scores_gemma":[0.9997796,0.00002459273,0.00002193278,0.00001454607,0.00001360802,0.00001700095,0.00001701074,0.00002739092,0.00008427197],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6457888,"threshold_uncertainty_score":0.8642333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01633009267020125,"score_gpt":0.2064000371427308,"score_spread":0.1900699444725296,"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."}}