{"id":"W2789959180","doi":"10.1186/s40623-018-0804-x","title":"Hydrology signal from GRACE gravity data in the Nelson River basin, Canada: a comparison of two approaches","year":2018,"lang":"en","type":"article","venue":"Earth Planets and Space","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alberta Innovates; National Natural Science Foundation of China","keywords":"Post-glacial rebound; Drainage basin; Structural basin; Geology; Geodesy; Global Positioning System; Hydrology (agriculture); Geomorphology; Glacial period; Geography; Geotechnical engineering; Cartography","routes":{"ca_aff":false,"ca_fund":true,"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":[0.000379762,0.0001157902,0.0002224523,0.0000247343,0.0001158219,0.00002870224,0.0003440451,0.0000402402,0.0001649647],"category_scores_gemma":[0.00001350783,0.00007932656,0.0000111372,0.000101063,0.0001743156,0.00008456604,0.0000284123,0.000158498,0.00001371952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001196343,"about_ca_system_score_gemma":0.00009331547,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.90061,"about_ca_topic_score_gemma":0.9768964,"domain_scores_codex":[0.998856,0.0001728463,0.0001545184,0.0002764797,0.0003102393,0.0002298812],"domain_scores_gemma":[0.9993354,0.0001634487,0.00008990248,0.0003296619,0.00001627514,0.00006532931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004082315,0.00002706189,0.989159,0.000005014343,0.00001537738,0.000007705517,0.0008147555,0.0002009753,0.0000188666,0.00004149427,0.001683922,0.007985031],"study_design_scores_gemma":[0.000318374,0.0001199881,0.9653737,0.000007727295,0.00001574041,0.000002835312,0.0002185817,0.02413458,0.00005979747,0.0006905757,0.008958533,0.00009956898],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972524,0.0003695829,0.00003132573,0.000619275,0.000112234,0.0001263173,0.0007497752,0.000003430507,0.0007356581],"genre_scores_gemma":[0.9986368,0.000006844434,0.000299456,0.0001881009,0.00009688199,2.347357e-7,0.000747785,0.000001637075,0.00002230657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0762864,"threshold_uncertainty_score":0.3234843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07420250640586175,"score_gpt":0.2434005752490425,"score_spread":0.1691980688431807,"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."}}