{"id":"W3093767035","doi":"10.1016/j.apenergy.2020.115888","title":"Impacts of climate change on photovoltaic energy potential: A case study of China","year":2020,"lang":"en","type":"article","venue":"Applied Energy","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Environmental science; Climate change; Representative Concentration Pathways; Renewable energy; Greenhouse gas; Photovoltaic system; Coupled model intercomparison project; Climatology; Climate model; Transient climate simulation; Sunshine duration; Atmospheric sciences; Meteorology; Geography; Precipitation; Engineering; Physics","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":[0.0005211189,0.0003749212,0.0003115394,0.0009196216,0.001096063,0.0009674942,0.0008173298,0.0009967991,0.001780174],"category_scores_gemma":[0.0006455901,0.0001953457,0.0006503791,0.002203915,0.0008717627,0.0006328549,0.0007895804,0.0003414679,0.000103045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003444798,"about_ca_system_score_gemma":0.001898061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1874083,"about_ca_topic_score_gemma":0.2503102,"domain_scores_codex":[0.9996829,0.00008280637,0.00001178317,0.00003366082,0.00006629476,0.0001226053],"domain_scores_gemma":[0.9996191,0.0001606951,0.00004984436,0.00003287753,0.00007447561,0.00006302606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009761767,0.00107914,0.5921891,0.0004445945,0.0005041379,0.04581632,0.004877647,0.265865,0.01364737,0.01223715,0.004606214,0.0577572],"study_design_scores_gemma":[0.000208289,0.0008091018,0.6486723,0.0001048986,0.0005556237,0.002828537,0.02649032,0.2893115,0.01012273,0.005326126,0.01537918,0.0001913875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961797,0.00007691076,0.0002542174,0.0001071779,0.000003664636,0.00001527245,0.0001092737,0.000009603541,0.003244127],"genre_scores_gemma":[0.998807,0.00008950445,0.0002045579,0.00001042234,0.000002001656,0.000004837923,0.00005199884,0.000002673481,0.0008269934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1874083,"threshold_uncertainty_score":0.3726349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02128401027628437,"score_gpt":0.2389337404294304,"score_spread":0.2176497301531461,"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."}}