{"id":"W4392091938","doi":"10.1016/j.scib.2024.02.023","title":"Natural lakes dominate global water storage variability","year":2024,"lang":"en","type":"article","venue":"Science Bulletin","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Natural (archaeology); Environmental science; Water storage; Geology; Oceanography; Paleontology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001781695,0.0001670045,0.0002036597,0.0003519018,0.0003325057,0.00111316,0.0001152099,0.0001183269,0.00376878],"category_scores_gemma":[0.0006096227,0.0001027528,0.0001023299,0.001451081,0.00033973,0.0009871451,0.000392394,0.000159731,0.0003017339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006152581,"about_ca_system_score_gemma":0.0009280643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0201579,"about_ca_topic_score_gemma":0.07191087,"domain_scores_codex":[0.9999288,0.000007376144,0.000005277347,0.00002031135,0.0000232746,0.00001495463],"domain_scores_gemma":[0.9997273,0.00007791365,0.00007053634,0.00002909327,0.0000673153,0.00002774077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001684478,0.00003931151,0.7222377,0.0002577342,0.0001311348,0.0003132373,0.001810239,0.004180561,0.01081366,0.01826099,0.009970434,0.2318166],"study_design_scores_gemma":[0.00001229546,0.00004072617,0.8989342,0.00005342103,0.00008256071,0.0001841219,0.002268322,0.003404127,0.001687724,0.004996677,0.08832279,0.00001303381],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9592293,0.002597593,0.001741632,0.0009652624,0.00005017445,0.00001920316,0.002034397,0.0001624771,0.03319991],"genre_scores_gemma":[0.9924125,0.001952734,0.000397309,0.0001078848,0.00003777838,0.000006134444,0.000567517,0.00003459599,0.00448369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0201579,"threshold_uncertainty_score":0.04008114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003774339008913691,"score_gpt":0.2174209912764968,"score_spread":0.2136466522675831,"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."}}