{"id":"W3087162689","doi":"10.5194/os-16-1067-2020","title":"Can the boundary profiles at 26° N be used to extract buoyancy-forced Atlantic Meridional Overturning Circulation signals?","year":2020,"lang":"en","type":"article","venue":"Ocean science","topic":"Climate variability and models","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020 Framework Programme; University of Reading; National Centre for Earth Observation; Natural Environment Research Council; Sight Research UK","keywords":"Ocean gyre; Geology; Buoyancy; Boundary current; Climatology; Thermohaline circulation; Forcing (mathematics); Atlantic Equatorial mode; Geostrophic wind; Oceanography; Equator; Shutdown of thermohaline circulation; Empirical orthogonal functions; Ocean current; North Atlantic Deep Water; Zonal and meridional; Ocean general circulation model; Latitude; Climate change; Geodesy; General Circulation Model; Subtropics; Mechanics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008461392,0.0001404176,0.0001273894,0.00002716146,0.0009160217,0.0001630336,0.0006047179,0.00003375957,0.001119555],"category_scores_gemma":[0.0003419098,0.0001029369,0.00005482405,0.0007520465,0.0006745405,0.0004380384,0.0004525518,0.0001253156,0.0001792028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002962424,"about_ca_system_score_gemma":0.0000981585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002347783,"about_ca_topic_score_gemma":0.0001139202,"domain_scores_codex":[0.9978054,0.00005553468,0.0002187258,0.0005792028,0.000930636,0.0004105182],"domain_scores_gemma":[0.9991872,0.0001442081,0.00008529407,0.0002883042,0.0000170347,0.0002779953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003851069,0.00003713151,0.1320153,0.00001516277,0.000004580249,0.000006488167,0.008356075,0.06743744,0.7892058,0.0004946722,0.001793019,0.0005957527],"study_design_scores_gemma":[0.0006177462,0.0002714642,0.425457,0.00007310519,0.00004452114,0.00004524944,0.000834717,0.5107432,0.03693465,0.001618521,0.02236303,0.0009968104],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857227,0.000007224439,0.0009078261,0.01158809,0.00009043721,0.0003527427,0.000013304,0.00007182659,0.001245877],"genre_scores_gemma":[0.9966906,0.000002198507,0.0004654537,0.002685093,0.0000497668,0.000005653053,0.000006450341,0.00001214853,0.00008264485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7522712,"threshold_uncertainty_score":0.9997935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04280584326497841,"score_gpt":0.2604956913486363,"score_spread":0.2176898480836578,"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."}}