{"id":"W4379520140","doi":"10.1038/s41597-023-02058-6","title":"A 100-member ensemble simulations of global historical (1951–2010) wave heights","year":2023,"lang":"en","type":"article","venue":"Scientific Data","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":3,"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; Scale (ratio); Submarine pipeline; Climate change; Environmental science; Temporal scales; Meteorology; Geography; Geology; Oceanography; Cartography","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":[0.001376664,0.0006152335,0.0007190956,0.0005015454,0.0005476698,0.0006017083,0.001072939,0.00109458,0.002094649],"category_scores_gemma":[0.0016079,0.0004200336,0.001323167,0.000806977,0.0004315365,0.0007418144,0.0005860413,0.001069107,0.0004041429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007618371,"about_ca_system_score_gemma":0.0008838595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04373709,"about_ca_topic_score_gemma":0.03508885,"domain_scores_codex":[0.9997688,0.00007086575,0.00001522212,0.00006892724,0.00003109133,0.00004503096],"domain_scores_gemma":[0.9990252,0.0003856457,0.00006351764,0.0002004093,0.0002104241,0.0001148599],"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":[0.0002273737,0.0001906974,0.02262061,0.00004080343,0.0002279773,0.00006794766,0.00003664865,0.9638634,0.0007517646,0.0007514535,0.004965036,0.00625637],"study_design_scores_gemma":[0.0001264603,0.00007943485,0.01795578,0.00001190542,0.00005835092,0.00001502614,0.00004714643,0.9788199,0.0005179939,0.0004690173,0.001869777,0.00002914444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9748617,0.0001300095,0.004885432,0.0002565448,0.0001156282,0.00003974257,0.01525694,0.0003652739,0.00408875],"genre_scores_gemma":[0.9689408,0.0000653194,0.005673566,0.00008316663,0.00003573604,0.00008656271,0.02429239,0.0000747284,0.0007477435],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.04373709,"threshold_uncertainty_score":0.08696502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1231029419150674,"score_gpt":0.2820808804544059,"score_spread":0.1589779385393385,"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."}}