{"id":"W2768390055","doi":"10.3390/en10111868","title":"An Integrated Modeling Approach for Forecasting Long-Term Energy Demand in Pakistan","year":2017,"lang":"en","type":"article","venue":"Energies","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Autoregressive integrated moving average; Demand forecasting; Fossil fuel; Economics; Renewable energy; Coal; Natural resource economics; Energy policy; Energy planning; Environmental economics; Time series; Engineering; Operations management; Computer science","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":[0.0005125029,0.0006014486,0.0004657914,0.0005821355,0.0004854824,0.001196177,0.0008328072,0.0007263401,0.00148131],"category_scores_gemma":[0.0008663693,0.0004034346,0.00069324,0.0007719991,0.0001573339,0.00071129,0.0005929563,0.0008632212,0.0002082167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002333,"about_ca_system_score_gemma":0.001565595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08636435,"about_ca_topic_score_gemma":0.05740181,"domain_scores_codex":[0.9997719,0.00005372957,0.00002022326,0.00006238251,0.00004872117,0.00004299378],"domain_scores_gemma":[0.9997268,0.0001072654,0.00004199974,0.00001034811,0.00009597211,0.00001768396],"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":[0.00007681896,0.00006978201,0.01282354,0.00004551841,0.0001025413,0.000231338,0.0001339228,0.9621649,0.0008185126,0.002751977,0.0009725766,0.01980849],"study_design_scores_gemma":[0.000003609694,0.00001572431,0.001394346,0.000003390308,0.00001404327,0.000009764259,0.00004749582,0.9976239,0.00008517021,0.0005159058,0.0002807219,0.000006024542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6824588,0.0009574943,0.2977386,0.001111514,0.0001780589,0.0001578529,0.002959964,0.0005570836,0.0138805],"genre_scores_gemma":[0.980645,0.0004044803,0.01606519,0.00003211719,0.00003078135,0.00006262518,0.0008032882,0.00001358442,0.001942878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08636435,"threshold_uncertainty_score":0.1717233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03449239613601321,"score_gpt":0.273608796486045,"score_spread":0.2391164003500318,"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."}}