{"id":"W2565914278","doi":"10.1109/pesgm.2017.8274137","title":"On the loadability sets of power systems — Part I: Characterization","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Characterization (materials science); Representation (politics); Mathematical optimization; Set (abstract data type); Electric power system; Computer science; Constraint (computer-aided design); Process (computing); Power (physics); 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":[0.002222398,0.001449045,0.0008354616,0.003277218,0.001260005,0.002994212,0.001648266,0.0008293446,0.007424739],"category_scores_gemma":[0.005906649,0.0005278026,0.001429258,0.002588222,0.002914345,0.006653975,0.002229415,0.003174636,0.001075872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00166574,"about_ca_system_score_gemma":0.0007216033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001404648,"about_ca_topic_score_gemma":0.0007117589,"domain_scores_codex":[0.9978122,0.0009347817,0.0001379307,0.0003424455,0.0005329488,0.0002395988],"domain_scores_gemma":[0.9964575,0.00228435,0.0003748327,0.0003653478,0.0004018757,0.0001159716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004475894,0.00004065162,0.0003493469,0.0001081479,0.00001561432,0.00007738292,0.0002301468,0.03413923,0.001880682,0.941413,0.001575443,0.02012548],"study_design_scores_gemma":[0.00001198846,0.00005701396,0.0004299529,0.00007130409,0.00001069964,0.0001159545,0.0001181894,0.1023351,0.001754312,0.8857622,0.009297852,0.00003543495],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02897806,0.0007856783,0.939344,0.0008238791,0.00006161048,0.000102184,0.0006773255,0.0001265689,0.02910064],"genre_scores_gemma":[0.6793153,0.001734394,0.3051215,0.0003329407,0.0006391409,0.0007969267,0.002053324,0.0002672631,0.009739232],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007424739,"threshold_uncertainty_score":0.02483821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135866057467496,"score_gpt":0.2175039338367094,"score_spread":0.2039173280899598,"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."}}