{"id":"W7130956803","doi":"10.3808/jeil.202400164","title":"Development of An Interval Chance-Constrained Mixed-Integer Linear Programming Model for Electric Power System Planning — A Case Study for the Province of Alberta, Canada","year":2025,"lang":"","type":"article","venue":"Journal of Environmental Informatics Letters","topic":"Electric Power System Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linear programming; Electric power system; Electricity generation; Electricity; Modular design; Interval (graph theory); Profit (economics); Key (lock); Mains electricity","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00111092,0.0003796169,0.0007389707,0.0003467828,0.0001972523,0.0000484592,0.0004424084,0.00009842924,0.000001480394],"category_scores_gemma":[0.00005975396,0.0003170033,0.0001964953,0.0002277869,0.00004888386,0.0004954446,0.00006375722,0.0003280914,9.241355e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001599639,"about_ca_system_score_gemma":0.0007754939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001027248,"about_ca_topic_score_gemma":0.003456313,"domain_scores_codex":[0.9957597,0.0000487572,0.003087772,0.000128238,0.0005065144,0.0004689804],"domain_scores_gemma":[0.9972341,0.0003990074,0.001907942,0.0002752361,0.00007701482,0.0001066988],"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":[0.0002666134,0.0002934659,0.0001697719,0.002072696,0.001421705,0.00005297848,0.0237586,0.9645425,0.001924735,0.00001043727,0.000149004,0.005337475],"study_design_scores_gemma":[0.001877218,0.0005437922,0.00003614365,0.0007847518,0.0003892278,0.0004617132,0.03778892,0.9544232,0.003300404,2.088491e-7,0.0001468083,0.0002476314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4857647,0.0001252752,0.5119704,0.00002871764,0.0003424138,0.001736476,0.00001898982,0.000004486099,0.000008516761],"genre_scores_gemma":[0.9507964,0.000003331704,0.04894491,0.00007131984,0.00003190937,0.00008747357,0.000006295885,0.00003698878,0.00002136378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4650317,"threshold_uncertainty_score":0.9999282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007688159295276665,"score_gpt":0.2162530669249106,"score_spread":0.208564907629634,"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."}}