{"id":"W4385343011","doi":"10.1038/s41597-023-02413-7","title":"Author Correction: A Database of Snow on Sea Ice in the Central Arctic Collected during the MOSAiC expedition","year":2023,"lang":"en","type":"erratum","venue":"Scientific Data","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Mosaic; Snow; Arctic; Sea ice; Oceanography; Physical geography; The arctic; Climatology; Geology; Geography; Meteorology; Archaeology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002093884,0.0002613612,0.0002679267,0.0002611131,0.0009719603,0.0003585275,0.002601767,0.0001570778,0.001020338],"category_scores_gemma":[0.001179241,0.0001586475,0.00006959925,0.00204985,0.000560509,0.0003928207,0.0002213217,0.001054896,0.0002565566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003474149,"about_ca_system_score_gemma":0.0005312021,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006047428,"about_ca_topic_score_gemma":0.03516088,"domain_scores_codex":[0.996491,0.0003872628,0.0004489146,0.0009163739,0.001158716,0.0005977372],"domain_scores_gemma":[0.9963727,0.0007894143,0.0003023663,0.002361878,0.00008353626,0.00009009286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004953906,0.00004467652,0.002920504,0.0001589685,0.0000217178,0.00004092376,0.0009227496,0.0002297014,0.000001348593,0.000008362289,0.994372,0.001229493],"study_design_scores_gemma":[0.0005724079,0.0001487863,0.3479373,0.001802266,0.0002038017,0.0001511963,0.009392619,0.1940013,0.000008766083,0.0002414832,0.4448782,0.0006618785],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"dataset","genre_scores_codex":[0.0568511,0.000760109,0.0003691979,0.009331566,0.6226315,0.004340938,0.2879553,0.0003722373,0.01738809],"genre_scores_gemma":[0.1753773,0.0002947579,0.000111435,0.0003038374,0.002790782,0.00001672008,0.424389,0.00003244864,0.3966838],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.6198407,"threshold_uncertainty_score":0.9998929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03512862446683904,"score_gpt":0.2545644915385897,"score_spread":0.2194358670717506,"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."}}