{"id":"W6892361582","doi":"10.5066/p9phpk4f","title":"CONUS404: Four-kilometer long-term regional hydroclimate reanalysis over the conterminous United States (ver. 3.0, June 2026)","year":2023,"lang":"en","type":"dataset","venue":"USGS DOI Tool Production Environment","topic":"","field":"","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weather Research and Forecasting Model; Forcing (mathematics); Climate model; Raw data; Water resources; Climate change; Hydrology (agriculture); Representation (politics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.002305619,0.001691717,0.001447017,0.001590479,0.0008722852,0.0004049775,0.001542416,0.000626136,0.003893598],"category_scores_gemma":[0.0003461881,0.001343143,0.0008302052,0.001494383,0.001291259,0.0005757997,0.001023858,0.001731016,0.0589713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001776267,"about_ca_system_score_gemma":0.0000882884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001028134,"about_ca_topic_score_gemma":0.0003571535,"domain_scores_codex":[0.9895787,0.001021168,0.001892445,0.003015366,0.003026472,0.001465805],"domain_scores_gemma":[0.9921222,0.0003618173,0.002014618,0.005075235,0.0001145748,0.0003115243],"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":[0.0003559203,0.0006300838,0.000338784,0.0002221974,0.002274557,0.0003006732,0.0001581471,0.00773133,0.0004085145,0.000001608394,0.9873381,0.0002400457],"study_design_scores_gemma":[0.001067457,0.000174784,0.01294861,0.0001926585,0.0028183,0.000251984,0.00009037584,0.0002479332,0.0001348905,0.00005600985,0.9804352,0.001581783],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04752642,0.0004633554,0.00001922673,0.003652104,0.002401963,0.00259951,0.9428931,0.0004321641,0.00001208769],"genre_scores_gemma":[0.0004470025,0.0074467,0.000041299,0.0008830674,0.001778727,0.0007228878,0.9669206,0.0004570939,0.0213026],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05507771,"threshold_uncertainty_score":0.9995829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03416817495034349,"score_gpt":0.2591256073269353,"score_spread":0.2249574323765919,"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."}}