{"id":"W2065155714","doi":"10.1175/jpo2987.1","title":"A Diagnosis of Thickness Fluxes in an Eddy-Resolving Model","year":2007,"lang":"en","type":"article","venue":"Journal of Physical Oceanography","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Foundation for Climate and Atmospheric Sciences; Deutsches Klimarechenzentrum","keywords":"Baroclinity; Isopycnal; Eddy; Eddy diffusion; Ocean gyre; Thermocline; Buoyancy; Stratification (seeds); Geology; Advection; Mechanics; Turbulence; Flux (metallurgy); Atmospheric sciences; Eddy covariance; Climatology; Physics; Thermodynamics; Subtropics; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007414896,0.0005928772,0.0002872605,0.0003248781,0.0003127121,0.0009154825,0.0005721484,0.0005666337,0.0002646768],"category_scores_gemma":[0.002756129,0.0005084606,0.0003041797,0.000191647,0.0003264426,0.0004569623,0.0003331403,0.0004203726,0.00006769765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006159513,"about_ca_system_score_gemma":0.000468709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009034825,"about_ca_topic_score_gemma":0.004709738,"domain_scores_codex":[0.9998814,0.00003693392,0.00001320167,0.00002761894,0.00002258403,0.00001822915],"domain_scores_gemma":[0.9995415,0.0002059617,0.000106354,0.00005171236,0.00006078943,0.0000336175],"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":[0.0001123711,0.00004038386,0.01495132,0.00001744436,0.00002892475,0.00008205922,0.00004504543,0.9672557,0.01223947,0.001758309,0.0000712433,0.003397777],"study_design_scores_gemma":[0.000008637469,0.00001411234,0.001261323,0.000002227403,0.000005988429,0.000004672697,0.000004021606,0.9969673,0.001535148,0.0001429038,0.00005053212,0.000003283307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9686442,0.00004837512,0.02914959,0.0001118295,0.000009330574,0.00002812687,0.0001360113,0.0001546076,0.001717873],"genre_scores_gemma":[0.9897648,0.00001861354,0.00983614,0.00001291718,0.000003266175,0.00001348414,0.00009739292,0.00001838956,0.0002350694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009034825,"threshold_uncertainty_score":0.01796442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01248685693433561,"score_gpt":0.2467882472560804,"score_spread":0.2343013903217448,"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."}}