{"id":"W1980903571","doi":"10.1007/s10584-013-0831-3","title":"Climate change projections of the North American Regional Climate Change Assessment Program (NARCCAP)","year":2013,"lang":"en","type":"article","venue":"Climatic Change","topic":"Climate variability and models","field":"Environmental Science","cited_by":201,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ouranos","funders":"Lawrence Livermore National Laboratory; Office of Science; National Oceanic and Atmospheric Administration; U.S. Environmental Protection Agency; U.S. Department of Energy; Commonwealth Scientific and Industrial Research Organisation; Office of Research and Development; National Science Foundation","keywords":"Climatology; Precipitation; Climate change; Climate model; Environmental science; General Circulation Model; GCM transcription factors; Geography; Meteorology; Geology; Oceanography","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005333297,0.0003687993,0.0004911069,0.00008581195,0.0004493046,0.00007270107,0.0006063889,0.00008569658,0.001583753],"category_scores_gemma":[0.00003322069,0.0002661675,0.0002590196,0.001044814,0.0008538742,0.0007423057,0.0009161708,0.0002968251,0.0004365745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002870928,"about_ca_system_score_gemma":0.00001304384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003372496,"about_ca_topic_score_gemma":0.002808917,"domain_scores_codex":[0.9968861,0.0002061996,0.0006332879,0.000609566,0.0006707148,0.0009940978],"domain_scores_gemma":[0.9980957,0.0001253497,0.0005556974,0.0009696541,0.00005017852,0.0002034157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002581213,0.001810632,0.8167994,0.0005332066,0.00003321767,0.00000256491,0.008271627,0.00001539115,0.0001590023,0.0007109514,0.0007477706,0.1708904],"study_design_scores_gemma":[0.0003561452,0.0003766475,0.9710124,0.0001755011,0.00008280989,0.00001188733,0.0007617213,0.02422429,0.00001035851,0.0002826275,0.002327251,0.0003783328],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806064,0.00003703584,0.00001370612,0.005438208,0.0003289471,0.006818315,0.0001475213,0.0001889723,0.006420847],"genre_scores_gemma":[0.9814639,0.001000528,0.003486725,0.00174389,0.0003013649,0.01184913,0.00006512112,0.00005184509,0.00003748737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1705121,"threshold_uncertainty_score":0.9999791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09284292661712636,"score_gpt":0.3156757493852297,"score_spread":0.2228328227681034,"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."}}