{"id":"W3198622062","doi":"10.1016/j.jconhyd.2021.103887","title":"Projections of meteorological drought based on CMIP6 multi-model ensemble: A case study of Henan Province, China","year":2021,"lang":"en","type":"article","venue":"Journal of Contaminant Hydrology","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada","keywords":"Downscaling; Precipitation; Environmental science; Coupled model intercomparison project; Climatology; Intensity (physics); Climate model; Climate change; Duration (music); Representative Concentration Pathways; Atmospheric sciences; Meteorology; Geography; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005499505,0.0008097104,0.0004112114,0.0007546192,0.0004972607,0.0005918525,0.0007281614,0.000813959,0.0008223954],"category_scores_gemma":[0.0006476825,0.0003018231,0.0006231608,0.001233876,0.0002883185,0.0005828803,0.0003989432,0.0003686706,0.00008866896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00218415,"about_ca_system_score_gemma":0.0022425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2996139,"about_ca_topic_score_gemma":0.2131257,"domain_scores_codex":[0.9998631,0.00002785112,0.000007246928,0.00003142808,0.00002668742,0.00004357954],"domain_scores_gemma":[0.9997727,0.00003661876,0.00002853444,0.00002259782,0.00008736944,0.00005218411],"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":[0.0002659321,0.0001673509,0.0699608,0.00006963236,0.0001999031,0.0007671274,0.0001181032,0.912332,0.002841579,0.0008877093,0.00246286,0.009927107],"study_design_scores_gemma":[0.00003871792,0.00003684184,0.05362862,0.00000536758,0.00006945141,0.00002960729,0.0001575723,0.9446168,0.0005355485,0.000258714,0.0005960677,0.00002665438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958949,0.00009345684,0.0008842938,0.0002262459,0.00001964204,0.00001164164,0.001775904,0.0001042622,0.0009897093],"genre_scores_gemma":[0.9978707,0.00006554075,0.0007043305,0.000009146478,0.000006483716,0.000008587144,0.001039597,0.000005690856,0.0002899299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2996139,"threshold_uncertainty_score":0.59574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01795911636816979,"score_gpt":0.2716779709459364,"score_spread":0.2537188545777666,"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."}}