{"id":"W2105361124","doi":"10.1002/2014gl061313","title":"Impact of Weddell Sea deep convection on natural and anthropogenic carbon in a climate model","year":2014,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Climate variability and models","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Oceanic and Atmospheric Administration; Sight Research UK; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research; Natural Environment Research Council; Princeton University","keywords":"Environmental science; Climate change; Convection; Climatology; Deep sea; Climate model; Atmospheric sciences; Oceanography; Deep convection; Carbon fibers; Carbon cycle; Geology; Meteorology; Ecosystem; Ecology; Geography; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007034914,0.0001098226,0.0001755075,0.00007927445,0.0000740479,0.00001836064,0.0001346959,0.00004948181,0.00004120759],"category_scores_gemma":[0.0001186904,0.00008958703,0.00007159855,0.0002703884,0.0005530313,0.0001112022,0.0002093594,0.0004004622,0.00003746738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002469102,"about_ca_system_score_gemma":0.000009317198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005381862,"about_ca_topic_score_gemma":0.0002277708,"domain_scores_codex":[0.9982362,0.0002345682,0.0001560203,0.0003584095,0.0004880407,0.000526771],"domain_scores_gemma":[0.9993024,0.0002971551,0.00002873796,0.0002499745,0.00001143672,0.0001103304],"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":[0.0006474454,0.0005655222,0.09048552,0.00006536391,0.00001993975,0.00000630259,0.000942196,0.1315426,0.7702403,0.0006119343,0.0001414089,0.00473148],"study_design_scores_gemma":[0.0003740471,0.000265547,0.15134,0.00001382147,0.000002651587,6.78117e-7,0.00001303955,0.8457717,0.000849563,0.001274033,0.000004044616,0.00009090879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984044,0.000004187901,0.0000729375,0.000591393,0.00002366653,0.0002004581,0.000005834526,0.0000112426,0.0006859258],"genre_scores_gemma":[0.9997318,0.00002574522,0.00006890233,0.0001129986,0.00002557635,0.00001242022,0.00000434526,0.00001001636,0.000008162293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7693908,"threshold_uncertainty_score":0.8135801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02577767806042372,"score_gpt":0.3256336788331523,"score_spread":0.2998560007727286,"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."}}