{"id":"W6979271264","doi":"","title":"Open Datasets for Grid Modeling and Visualization: An Alberta Power Network Case","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Toronto","funders":"","keywords":"Smart grid; Grid; Renewable energy; Variety (cybernetics); Network topology; Analytics; Electric power system; Electricity; Electricity generation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001822677,0.0008224385,0.0003558131,0.001851774,0.001100204,0.002224916,0.002451042,0.0011941,0.002598241],"category_scores_gemma":[0.006041961,0.000308676,0.0006598819,0.006464963,0.0009142848,0.001815717,0.001656635,0.001605551,0.0007576495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004276452,"about_ca_system_score_gemma":0.003432094,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4255529,"about_ca_topic_score_gemma":0.5553086,"domain_scores_codex":[0.9987805,0.0004246399,0.00006533953,0.0002109322,0.0003952009,0.0001232949],"domain_scores_gemma":[0.9974527,0.0008324777,0.0001352978,0.0007589141,0.0006267037,0.0001938666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006221599,0.0005346396,0.040557,0.0005552607,0.0002430236,0.001646637,0.0009590732,0.3828857,0.001769748,0.06100181,0.400501,0.108724],"study_design_scores_gemma":[0.0001915187,0.00004688178,0.02916919,0.0002471766,0.00005172368,0.0002900364,0.002027796,0.6989511,0.002708308,0.03806085,0.2281588,0.00009662888],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.4069227,0.002884777,0.1125598,0.01971242,0.001158782,0.0007126491,0.3796002,0.02415222,0.05229641],"genre_scores_gemma":[0.5746344,0.001245587,0.1073679,0.0007881858,0.0001161415,0.0002810496,0.308968,0.0009128196,0.005685875],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.5744472,"threshold_uncertainty_score":0.8461518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02923736059126976,"score_gpt":0.3098020083530905,"score_spread":0.2805646477618208,"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."}}