{"id":"W6889425422","doi":"10.25592/uhhfdm.17560","title":"Global Bias-Corrected CORDEX Datasets at Half Degree Resolution","year":2025,"lang":"en","type":"dataset","venue":"Universität Hamburg","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"NetCDF; Downscaling; Mean radiant temperature; Precipitation; Climate model; Data set; Relative humidity; Wind speed","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":[0.0007008641,0.001342184,0.0007588649,0.001630541,0.0006461423,0.001212781,0.001821629,0.000879817,0.02557427],"category_scores_gemma":[0.002072283,0.0004313255,0.0006718097,0.004184399,0.0003125809,0.000785038,0.0009094856,0.0007942137,0.02010828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00135185,"about_ca_system_score_gemma":0.001541792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09456773,"about_ca_topic_score_gemma":0.06806584,"domain_scores_codex":[0.999278,0.00008689,0.00006732946,0.0002270353,0.0002476448,0.00009317527],"domain_scores_gemma":[0.9984058,0.00008164415,0.0001039544,0.0004526275,0.0008741477,0.000081889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004196728,0.0001055614,0.01183185,0.0004777849,0.000189627,0.0001836032,0.0001143374,0.01127294,0.002386257,0.001957773,0.9506462,0.02041433],"study_design_scores_gemma":[0.0005436675,0.00004537215,0.06510304,0.0001739403,0.00006597612,0.0001056231,0.0001466231,0.01260707,0.006947029,0.001280731,0.9128886,0.00009235417],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01102536,0.0001317275,0.0006932229,0.000147181,0.0001184981,0.00007069443,0.9790618,0.00285016,0.005901299],"genre_scores_gemma":[0.01153742,0.00007566244,0.002193101,0.00006414385,0.00003023366,0.0001640115,0.9827484,0.0004470677,0.002740002],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09456773,"threshold_uncertainty_score":0.1880345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03605923594613753,"score_gpt":0.2662749473206868,"score_spread":0.2302157113745493,"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."}}