{"id":"W4393071716","doi":"10.1016/j.ejrh.2024.101746","title":"An aggregation framework to diagnose the compound hydroclimatic change of the Tibetan Plateau using multiple reanalysis data","year":2024,"lang":"en","type":"article","venue":"Journal of Hydrology Regional Studies","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Plateau (mathematics); Evapotranspiration; Climate change; Climatology; Environmental science; Surface runoff; Structural basin; Global warming; Water resources; Trend analysis; Geography; Hydrology (agriculture); Geology; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007120729,0.0001154342,0.0003182636,0.0000543009,0.0004486532,0.00003201551,0.0005842405,0.0000450052,0.00004909877],"category_scores_gemma":[0.0004038244,0.0000562313,0.0001133862,0.0005245053,0.000268796,0.0002620366,0.0000910336,0.0002234522,0.000004325979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001319605,"about_ca_system_score_gemma":0.00003577864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006700379,"about_ca_topic_score_gemma":0.004730246,"domain_scores_codex":[0.9987572,0.0001513835,0.0004250986,0.0001642316,0.0003366295,0.0001654133],"domain_scores_gemma":[0.9974605,0.001736338,0.0002855657,0.0003502486,0.0001210462,0.00004628925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008591014,0.00005851515,0.9352082,0.00005458913,0.001706474,0.00004601411,0.008278493,0.03980553,0.00003020658,0.0001778001,0.004882806,0.009665442],"study_design_scores_gemma":[0.0002333212,0.0004360542,0.6345102,0.0005049618,0.0009847673,0.0002260754,0.00558359,0.3262643,0.000008811073,0.007617916,0.0234195,0.000210512],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9544597,0.0294388,0.0003119526,0.01494941,0.0006341222,0.0001382161,0.00005119963,0.000006440694,0.00001020549],"genre_scores_gemma":[0.9947752,0.002367428,0.001333712,0.001006734,0.000491372,0.000001247809,0.00001205656,0.000003707799,0.00000853665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.300698,"threshold_uncertainty_score":0.3450723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2157080522986568,"score_gpt":0.357624791886378,"score_spread":0.1419167395877212,"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."}}