{"id":"W1479962539","doi":"10.3189/172756409787769753","title":"Glacier changes in Alaska: can mass-balance models explain GRACE mascon trends?","year":2009,"lang":"en","type":"article","venue":"Annals of Glaciology","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration; National Aeronautics and Space Administration","keywords":"Glacier; Precipitation; Series (stratigraphy); Climatology; Geology; Elevation (ballistics); Balance (ability); Glacier mass balance; Range (aeronautics); Environmental science; Atmospheric sciences; Meteorology; Geomorphology; Geography; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004099404,0.0001525933,0.0003199763,0.0001708854,0.00004330904,0.000009958261,0.0002233025,0.0001066171,0.0002010207],"category_scores_gemma":[0.00002117564,0.0001349342,0.00005970604,0.0002496962,0.00007582884,0.0001164931,0.000005803474,0.0001353681,0.00002677968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002132378,"about_ca_system_score_gemma":0.00002418051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009102337,"about_ca_topic_score_gemma":0.004965679,"domain_scores_codex":[0.998747,0.0001227903,0.0002204701,0.0002803562,0.0001799114,0.0004495043],"domain_scores_gemma":[0.9994746,0.00004871201,0.0001156854,0.0002111932,0.00005808374,0.00009165122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002437151,0.0001210051,0.8811224,0.00002255356,0.00004090805,0.00004235826,0.001027998,0.00570011,0.002182567,0.001542807,0.001566207,0.1063874],"study_design_scores_gemma":[0.00040578,0.0006253349,0.9386571,0.00002311323,0.000005652761,0.000003608944,0.00009321675,0.003239207,0.001643172,0.05392629,0.001162441,0.0002150902],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877723,0.0006365631,0.00002937531,0.00762122,0.0001568735,0.00008318387,0.00008898741,0.00001445031,0.003597048],"genre_scores_gemma":[0.9975114,0.0002670453,0.0001242116,0.001614354,0.00005446978,0.000001323538,0.0001101153,0.000002335946,0.0003146934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1061723,"threshold_uncertainty_score":0.5502458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06978494308569548,"score_gpt":0.2794882011071307,"score_spread":0.2097032580214352,"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."}}