{"id":"W4408899100","doi":"10.1080/07055900.2025.2478829","title":"Evaluation of a Multivariate Statistical Downscaling Method over Canada's Largest Pacific Basin","year":2025,"lang":"en","type":"article","venue":"ATMOSPHERE-OCEAN","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Environment and Climate Change Canada","keywords":"Downscaling; Multivariate statistics; Pacific basin; Structural basin; Climatology; Multivariate analysis; Geography; Statistics; Environmental science; Oceanography; Physical geography; Geology; Mathematics; Climate change; Geomorphology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.002607066,0.0001472273,0.0002331047,0.000003252981,0.0001053626,0.00002016779,0.0001701286,0.00008265189,0.004077113],"category_scores_gemma":[0.0005168198,0.0001371304,0.00004673037,0.0002641076,0.00008680593,0.00009517163,0.0001360668,0.0001274852,0.00001195791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005853479,"about_ca_system_score_gemma":0.0002586178,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5230187,"about_ca_topic_score_gemma":0.1838568,"domain_scores_codex":[0.9977318,0.0004576412,0.000362944,0.0003884149,0.0007790896,0.0002801192],"domain_scores_gemma":[0.9989823,0.0004339342,0.00009175338,0.0003505077,0.00005343344,0.00008805896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002181715,0.001031998,0.4108925,0.0001887099,0.0003281819,0.00001718452,0.001470058,0.3919915,0.006828771,0.02913157,0.03520637,0.122695],"study_design_scores_gemma":[0.001273935,0.00003376061,0.1797635,0.00005132873,0.0002970498,0.000001503785,0.0002575963,0.7908689,0.0008731295,0.01146098,0.01484649,0.0002717855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.915316,0.00003679319,0.05430086,0.0004311489,0.0002685869,0.0004890044,0.0001285353,0.00003297612,0.02899606],"genre_scores_gemma":[0.9698622,0.000003681769,0.02952813,0.0001720587,0.00001101586,0.00000513779,0.00002665042,0.00001079921,0.0003802991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3988774,"threshold_uncertainty_score":0.9968333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01823156626535968,"score_gpt":0.2964908485478396,"score_spread":0.2782592822824799,"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."}}