{"id":"W4220912670","doi":"10.46557/001c.32617","title":"An Empirical Analysis of the Impact of COVID-19 on the Power Sector of India","year":2022,"lang":"en","type":"article","venue":"Energy RESEARCH LETTERS","topic":"COVID-19 impact on air quality","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Market liquidity; Energy sector; Pandemic; Economics; Business; Clearing; Monetary economics; Emerging markets; Transmission (telecommunications); Distribution (mathematics); Development economics; International economics; Natural resource economics; Macroeconomics; Finance; Telecommunications","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":[0.0008021168,0.0002188228,0.000228002,0.0009332324,0.0004325905,0.001613573,0.0005415383,0.0004200091,0.002922922],"category_scores_gemma":[0.005053072,0.000164772,0.000463432,0.002299017,0.0007220167,0.0007648818,0.0008478024,0.001461729,0.0004479658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001354102,"about_ca_system_score_gemma":0.0009239963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08131541,"about_ca_topic_score_gemma":0.06152015,"domain_scores_codex":[0.9993388,0.0001545185,0.00003951173,0.00007105117,0.0001138777,0.0002821525],"domain_scores_gemma":[0.9899145,0.004637817,0.003272553,0.0003935935,0.0009525616,0.0008289937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001166059,0.0001004273,0.9866666,0.00003799906,0.00008800963,0.0004619273,0.0003195982,0.005364385,0.0002448648,0.0008798961,0.0016611,0.004058668],"study_design_scores_gemma":[0.000007038647,0.00008083386,0.9874878,0.0000191356,0.00005858588,0.0001757371,0.00193736,0.008221929,0.0003263304,0.0002108891,0.001460773,0.00001349598],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954206,0.0001899097,0.0001545142,0.0004500161,0.000006822689,0.000008784248,0.0009460485,0.00001184622,0.002811374],"genre_scores_gemma":[0.9984198,0.0001429609,0.00003363699,0.00003519308,0.000009714597,0.000003191139,0.0008814854,0.000002655506,0.0004712759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08131541,"threshold_uncertainty_score":0.1616842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09697218590425292,"score_gpt":0.440467127059459,"score_spread":0.3434949411552061,"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."}}