{"id":"W4405560967","doi":"10.1002/joc.8726","title":"Monthly High‐Resolution Historical Climate Data for North America Since 1901","year":2024,"lang":"en","type":"article","venue":"International Journal of Climatology","topic":"Climate variability and models","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Alberta; University of British Columbia","funders":"","keywords":"Overfitting; Downscaling; Grid; Climatology; Climate change; Meteorology; Environmental science; Computer science; Geography; Geology; Geodesy; Precipitation","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":[0.000402086,0.000211609,0.0001889094,0.001544077,0.0002180875,0.000357285,0.0003202534,0.0001619964,0.00456539],"category_scores_gemma":[0.001108801,0.0001457451,0.0001764949,0.003571877,0.0001090289,0.0003380231,0.0003365574,0.000413931,0.001105013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005414606,"about_ca_system_score_gemma":0.0005653939,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07932422,"about_ca_topic_score_gemma":0.1034833,"domain_scores_codex":[0.9997677,0.00004645965,0.000020593,0.00006691726,0.00007623265,0.00002203402],"domain_scores_gemma":[0.999137,0.0001155778,0.0001578518,0.0001457158,0.000394611,0.00004936519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002910387,0.0002425104,0.4956909,0.0008355379,0.0004588093,0.0003005059,0.00161239,0.07473513,0.005395371,0.003421198,0.222619,0.1943976],"study_design_scores_gemma":[0.00002834896,0.00003373624,0.8655189,0.00005029889,0.0000456646,0.00007032779,0.0002848176,0.007687064,0.001061399,0.0005654637,0.1246219,0.00003210504],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.4050898,0.000653669,0.007441434,0.0004381781,0.0001282647,0.00007801723,0.568803,0.001134088,0.0162335],"genre_scores_gemma":[0.5786984,0.0007073061,0.0205125,0.00007534063,0.00009163818,0.0003139052,0.3945581,0.0002139425,0.004828998],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9206758,"threshold_uncertainty_score":0.157725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03376017461080066,"score_gpt":0.2996409885858613,"score_spread":0.2658808139750606,"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."}}