{"id":"W4415595803","doi":"10.5194/tc-19-5111-2025","title":"Combining observational data and numerical models to obtain a seamless high-temporal-resolution seasonal cycle of snow and ice mass balance at the MOSAiC Central Observatory","year":2025,"lang":"en","type":"article","venue":"˜The œcryosphere","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Norges Forskningsråd; National Science Council; National Aeronautics and Space Administration; Canadian Space Agency; National Science Foundation","keywords":"Snow; Sea ice; Arctic ice pack; Arctic; Cryosphere; Antarctic sea ice; Sea ice thickness; Snow field","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003895324,0.0001830104,0.0002489585,0.000007076872,0.0006615414,0.00007202665,0.0004955947,0.00006565866,0.000211855],"category_scores_gemma":[0.00005038173,0.0001243155,0.00003480457,0.0004545745,0.0002115537,0.0002593349,0.0002551503,0.0001651205,0.000006110583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002133755,"about_ca_system_score_gemma":0.0001194013,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006961915,"about_ca_topic_score_gemma":0.009605142,"domain_scores_codex":[0.9984579,0.0001221051,0.0003024203,0.000419139,0.0003390909,0.0003593637],"domain_scores_gemma":[0.9985806,0.0006228889,0.0001213777,0.0004848119,0.0000795051,0.000110762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009643102,0.00002210918,0.9267742,0.00003871181,0.0000753468,0.000002045496,0.0004043876,0.05004403,0.00001943374,0.002090297,0.0139478,0.006485184],"study_design_scores_gemma":[0.0002296543,0.00002352629,0.574746,0.00003481137,0.00002828939,0.000001780805,0.0005059,0.412076,0.000002303274,0.001498587,0.01075711,0.00009609338],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731857,0.005225735,0.01371512,0.00581511,0.0003258745,0.0004395242,0.0009843142,0.00003592377,0.0002727559],"genre_scores_gemma":[0.9941996,0.0001494023,0.002840773,0.001449714,0.00007189078,0.000009095515,0.0004612226,0.00000606358,0.0008122262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.362032,"threshold_uncertainty_score":0.9996508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03951294959638995,"score_gpt":0.2412382602465548,"score_spread":0.2017253106501649,"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."}}