{"id":"W2764200753","doi":"10.1002/2017wr021585","title":"Nine Hundred Years of Weekly Streamflows: Stochastic Downscaling of Ensemble Tree‐Ring Reconstructions","year":2017,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Alberta Innovates","keywords":"Streamflow; Dendrochronology; Climatology; Proxy (statistics); Downscaling; Range (aeronautics); Historical record; Series (stratigraphy); Environmental science; Data assimilation; Climate change; Geology; Drainage basin; Meteorology; Geography; Statistics; Mathematics; Oceanography; Cartography; History","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0009627641,0.0001850189,0.0002537,0.000807112,0.0002457509,0.0004477676,0.0004694521,0.000253373,0.0005443674],"category_scores_gemma":[0.002550401,0.0002104903,0.0003606581,0.0007613705,0.0001607391,0.0003299271,0.000246112,0.0003260458,0.0001141791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005988138,"about_ca_system_score_gemma":0.0006570779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06132912,"about_ca_topic_score_gemma":0.1034683,"domain_scores_codex":[0.9998493,0.00003269931,0.000009138763,0.00004678447,0.00004137852,0.00002067032],"domain_scores_gemma":[0.9992456,0.000217028,0.0000993744,0.0001669121,0.0002200212,0.00005106772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001120505,0.00007439851,0.1901247,0.00001900324,0.0002344019,0.00008000725,0.0001253353,0.7418144,0.003414348,0.0007366844,0.001020207,0.06224443],"study_design_scores_gemma":[0.000008066385,0.00001558075,0.0676109,0.000006998746,0.00002419594,0.00001546742,0.00002683589,0.9303104,0.0009597646,0.0003777044,0.0006298271,0.0000141487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772784,0.00007726839,0.02108827,0.00004016874,0.00001519944,0.00001150262,0.0006726148,0.0003111817,0.0005054275],"genre_scores_gemma":[0.989902,0.00002978987,0.008596997,0.00000887511,0.000006678209,0.000008330098,0.001274279,0.00003121133,0.0001417406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06132912,"threshold_uncertainty_score":0.1219443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06527217510855227,"score_gpt":0.3129209446927878,"score_spread":0.2476487695842355,"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."}}