{"id":"W3155442134","doi":"10.1029/2020gl092147","title":"Long‐Range Forecasting as a Past Value Problem: Untangling Correlations and Causality With Scaling","year":2021,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Climate variability and models","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Teleconnection; Causality (physics); Granger causality; Econometrics; Range (aeronautics); Statistical physics; Multivariate statistics; Scaling; Climatology; Mathematics; Statistics; Physics; Geology; El Niño Southern Oscillation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.005127471,0.0005691685,0.001001202,0.001019364,0.0008778872,0.002427557,0.00105912,0.001538309,0.002338853],"category_scores_gemma":[0.0265187,0.000583234,0.0007990089,0.00142701,0.003089942,0.004759754,0.001538407,0.002582702,0.00009636156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001407972,"about_ca_system_score_gemma":0.001257453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008588238,"about_ca_topic_score_gemma":0.003714544,"domain_scores_codex":[0.9987753,0.0006948104,0.00007147624,0.0002358454,0.0001439446,0.00007861516],"domain_scores_gemma":[0.9747995,0.02126756,0.001826826,0.0008840393,0.0007367026,0.0004852865],"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":[0.00003210587,0.00003399316,0.003944863,0.00004303613,0.00005085521,0.0001301148,0.00009448687,0.6404251,0.0001353409,0.3439531,0.001320955,0.009836125],"study_design_scores_gemma":[0.000005485406,0.000004291238,0.0002933482,0.000007535294,0.000003152489,0.000008376779,0.0000135802,0.7814994,0.00002885347,0.2179147,0.0002146245,0.000006664604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1991383,0.001607679,0.7793908,0.008546164,0.0002762619,0.00004696937,0.0003431563,0.0001875198,0.01046322],"genre_scores_gemma":[0.963405,0.000623723,0.03380391,0.0002195472,0.0002607034,0.00006455631,0.00012175,0.00004294591,0.001457849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008588238,"threshold_uncertainty_score":0.02711701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06079440869520228,"score_gpt":0.3077161458511968,"score_spread":0.2469217371559946,"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."}}