{"id":"W1963980632","doi":"10.1002/joc.1395","title":"Lagged relationships between North American snow mass and atmospheric teleconnection indices","year":2006,"lang":"en","type":"article","venue":"International Journal of Climatology","topic":"Climate variability and models","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration; Northwestern University","keywords":"Teleconnection; Climatology; North Atlantic oscillation; Snow; Pacific decadal oscillation; El Niño Southern Oscillation; Environmental science; Principal component analysis; Spatial ecology; Geography; Physical geography; Geology; Meteorology","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":[],"consensus_categories":[],"category_scores_codex":[0.0003487171,0.00008265577,0.0001921617,0.00003386801,0.00007630175,0.00003045413,0.000199115,0.00004772391,0.0001981691],"category_scores_gemma":[0.000153987,0.00007508186,0.00005128181,0.0001345758,0.0002318682,0.0002774423,0.00005935614,0.0002321634,0.00003292914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001081105,"about_ca_system_score_gemma":0.00001281073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003267161,"about_ca_topic_score_gemma":0.001098201,"domain_scores_codex":[0.9989254,0.0001217829,0.0004391092,0.0001316291,0.0002468747,0.0001351754],"domain_scores_gemma":[0.9989461,0.000399073,0.0004882038,0.00006388109,0.00004471277,0.00005798657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003371337,0.0000386413,0.994802,0.000001550978,0.00002860813,0.0000141661,0.00008601748,0.001891188,0.0001411921,0.0003513262,0.0001814185,0.002430161],"study_design_scores_gemma":[0.0003522225,0.00008383831,0.9903581,0.00000686261,0.00002535668,0.0002103658,0.00008088343,0.0009801963,0.00007591063,0.005056069,0.002687445,0.00008274979],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928749,0.00001784705,0.003512595,0.001678354,0.000216921,0.00004335634,0.000008971602,0.00001057101,0.001636479],"genre_scores_gemma":[0.9950565,0.00005504591,0.004634609,0.00007517281,0.0001311221,0.000001647709,0.0000112276,0.000006668347,0.00002801009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004704743,"threshold_uncertainty_score":0.3061749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01494901875652477,"score_gpt":0.250717197769715,"score_spread":0.2357681790131902,"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."}}