{"id":"W7015436486","doi":"","title":"South Asia's power generation and cross-border power trading","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Per capita; Consumption (sociology); Quarter (Canadian coin); Indigenous; Power (physics); Electric power; Electricity generation; Economic power","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002745107,0.0003656676,0.0001563812,0.0005922574,0.0005836244,0.00257043,0.0002729089,0.0004344029,0.02289274],"category_scores_gemma":[0.0003793757,0.000112679,0.0002605904,0.001612449,0.0006343549,0.001674724,0.001461422,0.0007099176,0.002622942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000738877,"about_ca_system_score_gemma":0.0009237846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002375976,"about_ca_topic_score_gemma":0.003343453,"domain_scores_codex":[0.9998869,0.00001884387,0.000007304434,0.00001965176,0.00003783494,0.00002961726],"domain_scores_gemma":[0.9998111,0.00005738721,0.00003883624,0.00001883454,0.00005136093,0.00002245467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001122425,0.0000790003,0.01929544,0.002005855,0.0001054265,0.002961093,0.003625059,0.005285445,0.008636924,0.2001708,0.05244756,0.7052751],"study_design_scores_gemma":[0.00001272571,0.0001173721,0.02773121,0.0008349318,0.0000514185,0.00290927,0.00385638,0.002307762,0.00380373,0.04402563,0.9143117,0.00003786441],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09593169,0.05350676,0.01749526,0.01056415,0.0009738026,0.0001275836,0.0009898291,0.0002990957,0.8201118],"genre_scores_gemma":[0.805212,0.06993791,0.005590101,0.001644814,0.0004716547,0.00007421653,0.0008279274,0.0001332707,0.1161081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02289274,"threshold_uncertainty_score":0.07658386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0165344267623386,"score_gpt":0.2733395145911645,"score_spread":0.2568050878288259,"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."}}