{"id":"W3159977276","doi":"10.5194/egusphere-egu2020-11625","title":"AMOC recovery in a multi-centennial scenario using a coupled atmosphere-ocean-ice sheet model","year":2020,"lang":"en","type":"article","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Meltwater; Ice sheet; Climatology; Climate model; Ocean current; Antarctic ice sheet; Oceanography; Sink (geography); Lead (geology); Geology; Environmental science; North Atlantic Deep Water; Greenland ice sheet; Sea ice; Cryosphere; Thermohaline circulation; Climate change; Snow; Geography; Geomorphology","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":[0.0005703318,0.000834415,0.0005993071,0.0005356228,0.0005449171,0.001065408,0.001059799,0.001722611,0.001495101],"category_scores_gemma":[0.001231133,0.0003547538,0.001106501,0.0006213493,0.0006249907,0.0007006544,0.0005712533,0.000959159,0.0001678625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001315713,"about_ca_system_score_gemma":0.0008760673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08915461,"about_ca_topic_score_gemma":0.04673518,"domain_scores_codex":[0.9998322,0.00006233168,0.00001127177,0.00003879168,0.00001358302,0.00004172795],"domain_scores_gemma":[0.9993966,0.0002644262,0.00007368594,0.00005937751,0.0000995916,0.0001063927],"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":[0.0003149311,0.0001329165,0.0138704,0.00004341338,0.0001597598,0.000213914,0.00004402014,0.9807421,0.001643468,0.0006183622,0.0009687568,0.001247872],"study_design_scores_gemma":[0.0001185136,0.00007175207,0.006606395,0.00001000204,0.00005621297,0.00001408218,0.00006135342,0.9921713,0.0003724682,0.0002409579,0.0002542578,0.00002269326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948847,0.0001260418,0.0008712804,0.0003302159,0.00004112981,0.00001578826,0.001416624,0.0001379695,0.002176262],"genre_scores_gemma":[0.9971731,0.00005923721,0.0009363008,0.00005622132,0.00001008517,0.00002197556,0.001301678,0.00002894387,0.0004123714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08915461,"threshold_uncertainty_score":0.1772713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07356459636792348,"score_gpt":0.2446650080996591,"score_spread":0.1711004117317356,"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."}}