{"id":"W4412380995","doi":"10.5194/esd-16-1001-2025","title":"A multi-model analysis of the decadal prediction skill for the North Atlantic ocean heat content","year":2025,"lang":"en","type":"article","venue":"Earth System Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"HORIZON EUROPE European Research Council; Natural Environment Research Council; Fundação para a Ciência e a Tecnologia; Ministerio de Economía y Competitividad; UK Research and Innovation","keywords":"Ocean heat content; Climatology; Environmental science; Oceanography; Geology; Thermohaline circulation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001349919,0.0003963461,0.0002976538,0.0003622601,0.000250094,0.0006403073,0.0003895677,0.0003328971,0.0007199967],"category_scores_gemma":[0.001935775,0.0001846974,0.0008639506,0.0003177856,0.0001936854,0.0004762952,0.0005522573,0.0006606854,0.0001062552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004798861,"about_ca_system_score_gemma":0.000483963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0239198,"about_ca_topic_score_gemma":0.01814473,"domain_scores_codex":[0.9998455,0.00005156672,0.00001209618,0.00005014633,0.00001830524,0.00002239137],"domain_scores_gemma":[0.9991243,0.0004470945,0.0001051157,0.0001367546,0.0001259422,0.00006070232],"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":[0.0003578146,0.0001747413,0.2672282,0.00005918079,0.0009187311,0.0001057114,0.00007241329,0.7072587,0.005241901,0.001007768,0.001565234,0.01600964],"study_design_scores_gemma":[0.00002029817,0.0000903724,0.08910517,0.00000804582,0.00009919145,0.00001634722,0.00005403422,0.9084864,0.001368766,0.0003292233,0.0004032375,0.00001888354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963822,0.00009233175,0.002031847,0.0001170538,0.00001838392,0.000005649622,0.0006537547,0.00008554697,0.0006130851],"genre_scores_gemma":[0.9986116,0.00002281365,0.0005705617,0.00001402456,0.000005662468,0.000004940815,0.0006296397,0.00001219277,0.0001285802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0239198,"threshold_uncertainty_score":0.04756111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01889194110347465,"score_gpt":0.2285274563949099,"score_spread":0.2096355152914352,"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."}}