{"id":"W4376278676","doi":"10.5194/tc-17-2021-2023","title":"Chemical and visual characterisation of EGRIP glacial ice and cloudy bands within","year":2023,"lang":"en","type":"article","venue":"˜The œcryosphere","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Office of Polar Programs; Horizon 2020; Helmholtz Association; Universitetet i Bergen; Institut Polaire Français Paul Emile Victor; Beijing Normal University; National Institute of Polar Research; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; European Commission; H2020 Marie Skłodowska-Curie Actions; Trond Mohn stiftelse; Chinese Academy of Sciences; Deutscher Akademischer Austauschdienst; Villum Fonden; National Science Foundation","keywords":"Geology; Ice core; Mineralogy; Ice sheet; Geomorphology; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002058812,0.00009863074,0.0001457905,0.000006686272,0.0001878271,0.00003589558,0.00007440864,0.00005461341,0.0004109996],"category_scores_gemma":[0.0000264214,0.00006860757,0.00002538416,0.0002833708,0.0001378755,0.0000851629,0.00003001259,0.00009145749,0.00002876378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002071208,"about_ca_system_score_gemma":0.00001817662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001109242,"about_ca_topic_score_gemma":0.002287127,"domain_scores_codex":[0.9992945,0.00002708068,0.0001891198,0.0001711298,0.0001576731,0.0001604613],"domain_scores_gemma":[0.9996083,0.0001510133,0.00008145763,0.00008252994,0.00003083649,0.00004579546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009044535,0.00001682448,0.9190997,0.0000440093,0.00004627795,0.000003804549,0.002588135,0.00008385857,0.0008992318,0.0001012776,0.001476937,0.07554946],"study_design_scores_gemma":[0.0002259703,0.00005336434,0.982063,0.00001017051,0.00002077913,0.000004034257,0.001184333,0.01182264,0.00006017433,0.0002090238,0.00425178,0.00009471317],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983109,0.000517944,0.00001812609,0.0003275447,0.000230952,0.0001190734,0.00002918251,0.0000382613,0.00040798],"genre_scores_gemma":[0.9990681,0.0001558178,0.00007991151,0.0001471751,0.0001433895,0.000002264605,0.00005064884,0.000003618541,0.0003490405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07545475,"threshold_uncertainty_score":0.4500158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583150398016336,"score_gpt":0.226350083489817,"score_spread":0.2105185795096537,"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."}}