{"id":"W2066841193","doi":"10.1016/j.jhydrol.2014.11.049","title":"Dendrohydrology in Canada’s western interior and applications to water resource management","year":2014,"lang":"en","type":"article","venue":"Journal of Hydrology","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Regina","funders":"National Integrated Drought Information System; Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Streamflow; Preparedness; Water resources; Dendrochronology; Environmental resource management; Population; Proxy (statistics); Resource (disambiguation); Geography; Environmental science; Hydrology (agriculture); Water resource management; Drainage basin; Geology; Ecology; Computer science; Political science","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":[0.0002379112,0.000176627,0.00019136,0.001449861,0.001928416,0.001809978,0.0004059618,0.0002378039,0.002343042],"category_scores_gemma":[0.0009797604,0.0001209849,0.0002060143,0.00454864,0.0005886059,0.0003507877,0.0005033001,0.000349225,0.0001251093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01492309,"about_ca_system_score_gemma":0.01639041,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.992559,"about_ca_topic_score_gemma":0.9972849,"domain_scores_codex":[0.9999169,0.000008883385,0.000003906187,0.00001603681,0.00002177516,0.00003239555],"domain_scores_gemma":[0.9995508,0.0000595001,0.00002992472,0.00001292764,0.0002442498,0.000102646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001251104,0.00007899008,0.8340527,0.0001622358,0.00007708628,0.0005247599,0.003205419,0.02948257,0.001829886,0.01041633,0.009985979,0.110059],"study_design_scores_gemma":[0.00001142129,0.00001270505,0.9383612,0.00007463771,0.00003007356,0.00008415281,0.00738802,0.02515146,0.0004984135,0.002264068,0.02608382,0.00004008819],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9592285,0.002520976,0.003195376,0.001994895,0.0000527686,0.0000503305,0.005008516,0.0001623113,0.02778635],"genre_scores_gemma":[0.9926111,0.001178105,0.00186594,0.0000483455,0.0000111694,0.000007466965,0.0006223588,0.00001969057,0.003635931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01492309,"threshold_uncertainty_score":0.1082751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007865193807677365,"score_gpt":0.2119658951731633,"score_spread":0.204100701365486,"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."}}