{"id":"W2556982837","doi":"10.1002/2016jd025533","title":"Wavelet analysis of precipitation extremes over Canadian ecoregions and teleconnections to large‐scale climate anomalies","year":2016,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Climate variability and models","field":"Environmental Science","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; University of Alberta","keywords":"Teleconnection; Climatology; Pacific decadal oscillation; Precipitation; Environmental science; North Atlantic oscillation; El Niño Southern Oscillation; Atmospheric sciences; Geography; Geology; Meteorology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000924491,0.00008967234,0.0002741961,0.0000895827,0.0002095694,0.0000376368,0.0001958504,0.0000534325,0.001704322],"category_scores_gemma":[0.0005194003,0.00006001048,0.0001430159,0.0009187183,0.0002472344,0.0003370416,0.0001429828,0.0001457119,0.0000448897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002394963,"about_ca_system_score_gemma":0.00007499847,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02163589,"about_ca_topic_score_gemma":0.2683084,"domain_scores_codex":[0.9983053,0.0001754264,0.0003347482,0.0002032077,0.0005124703,0.0004688572],"domain_scores_gemma":[0.998362,0.0007351161,0.0001040228,0.0002032048,0.0001302123,0.000465454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003863736,0.0007792692,0.9111639,0.0000363338,0.0006462451,0.00002139044,0.003889616,0.002287766,0.04793689,0.0038468,0.007886377,0.02111901],"study_design_scores_gemma":[0.0002919608,0.0004148491,0.9870422,0.000040088,0.0001052529,0.00000238279,0.0005509086,0.00332275,0.0003503409,0.003749571,0.004029619,0.0001000246],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967923,0.00001932427,0.0004463945,0.001460631,0.00003122456,0.0001198706,0.00008677554,0.000003621643,0.001039918],"genre_scores_gemma":[0.9980959,0.0001417109,0.001363987,0.00004601501,0.00004401496,0.000006368702,0.000001736396,0.000007742412,0.0002925758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2466725,"threshold_uncertainty_score":0.9992083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02892821901625553,"score_gpt":0.3098557879323225,"score_spread":0.280927568916067,"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."}}