{"id":"W4285495309","doi":"10.3389/fmars.2022.847017","title":"Effects of Internal Climate Variability on Historical Ocean Wave Height Trend Assessment","year":2022,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Japan Agency for Marine-Earth Science and Technology; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Climatology; Ensemble average; Statistic; Environmental science; Climate change; Climate model; Realization (probability); Significant wave height; Meteorology; Wind wave; Statistics; Geography; Geology; Mathematics; Oceanography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001527957,0.0001169353,0.0002266254,0.0002864754,0.0002863161,0.00002906268,0.0003718451,0.00002100661,0.000206454],"category_scores_gemma":[0.00008000345,0.00009607059,0.00005866475,0.0007266579,0.0002541628,0.0001334201,0.0002093852,0.0003120001,0.000001107715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002389948,"about_ca_system_score_gemma":0.0001008687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003707948,"about_ca_topic_score_gemma":0.0000188925,"domain_scores_codex":[0.998091,0.0001787958,0.0002672291,0.0004175985,0.0006509391,0.000394401],"domain_scores_gemma":[0.9994102,0.0001316494,0.0001147243,0.000213936,0.00001678317,0.0001127319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009705396,0.00011404,0.8632229,0.00004388104,0.000005810916,0.00007628746,0.0002007104,0.003404016,0.00007707276,0.0001220647,0.0009990258,0.1316372],"study_design_scores_gemma":[0.0003621074,0.0004559639,0.8653539,0.00001530717,0.000008052629,0.00001483256,0.0001180688,0.1294391,0.0002615311,0.002244513,0.001568998,0.0001576106],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757344,0.00002822205,0.0002958691,0.0001313651,0.00440618,0.0001672535,0.00001401534,0.00001735126,0.0192053],"genre_scores_gemma":[0.9689727,0.00001564524,0.03065246,0.00009662886,0.00004519933,3.278664e-8,0.000008577269,0.000002607256,0.0002060979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1314795,"threshold_uncertainty_score":0.3917645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005268152591534999,"score_gpt":0.2005971444489693,"score_spread":0.1953289918574343,"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."}}