{"id":"W4306691474","doi":"10.5194/egusphere-2022-861","title":"Underestimation of oceanic carbon uptake in the Arctic Ocean: Ice melt as predictor of the sea ice carbon pump","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada; Dalhousie University","funders":"Horizon 2020; Ocean Frontier Institute; Norges Forskningsråd; Natural Sciences and Engineering Research Council of Canada; European Commission; Office of Polar Programs; Commonwealth Scientific and Industrial Research Organisation; National Science Foundation","keywords":"Sea ice; Arctic ice pack; Environmental science; Sea ice thickness; Carbon cycle; Arctic sea ice decline; Oceanography; Sea ice concentration; Antarctic sea ice; Arctic; Arctic geoengineering; Alkalinity; Seawater; Biogeochemical cycle; Drift ice; Cryosphere; Carbon dioxide; Sea ice growth processes; Geology; Chemistry; Environmental chemistry; Ecology; Ecosystem; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001018726,0.0005482467,0.0004019275,0.0005362925,0.0002678638,0.0008877161,0.0002773609,0.0005727155,0.0004132497],"category_scores_gemma":[0.002409982,0.0002279644,0.000647124,0.0006354921,0.0003288171,0.0005919235,0.0005299945,0.0003781996,0.0001014241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008112232,"about_ca_system_score_gemma":0.000529377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02679446,"about_ca_topic_score_gemma":0.01182323,"domain_scores_codex":[0.9997972,0.00007112776,0.0000152506,0.00004357305,0.00003388679,0.00003901273],"domain_scores_gemma":[0.9989937,0.0005225015,0.0001840199,0.00007611866,0.0001580309,0.00006565632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004666586,0.0000737069,0.5985293,0.0001269628,0.0003528947,0.000203052,0.00007960646,0.380845,0.0120001,0.0005920373,0.0003364132,0.006394253],"study_design_scores_gemma":[0.00002773778,0.0001177456,0.3279334,0.00003423656,0.0001169889,0.00006772953,0.0001165742,0.6640199,0.006492616,0.0005505104,0.0004873787,0.00003524134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975657,0.0001921597,0.001318515,0.00007984056,0.00001106958,0.000002953328,0.0003842012,0.0000383391,0.0004071968],"genre_scores_gemma":[0.9993713,0.00004494435,0.0002780777,0.000008283106,0.000003299933,0.000001922814,0.0002520276,0.000005889532,0.00003419746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02679446,"threshold_uncertainty_score":0.05327702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01559185544859385,"score_gpt":0.223524473247831,"score_spread":0.2079326177992371,"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."}}