{"id":"W2048606854","doi":"10.1002/esp.1822","title":"Remote sensing of volumetric storage changes in lakes","year":2009,"lang":"en","type":"article","venue":"Earth Surface Processes and Landforms","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bathymetry; Hydrology (agriculture); Stage (stratigraphy); Water storage; Altimeter; Geology; Environmental science; Remote sensing; Water level; Surface water; Physical geography; Oceanography; Geography; Geotechnical engineering; Paleontology; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009336478,0.0001353271,0.0001144741,0.0007360426,0.0002383817,0.0003689922,0.0001956753,0.00008933707,0.0005252974],"category_scores_gemma":[0.0003613493,0.0001163189,0.0001163865,0.0008002292,0.0002134414,0.0002122149,0.0002385872,0.00007229114,0.00005515083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001009041,"about_ca_system_score_gemma":0.000406772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1467973,"about_ca_topic_score_gemma":0.1888386,"domain_scores_codex":[0.9999626,0.000004270611,0.000002090596,0.000007789003,0.00001514069,0.0000080723],"domain_scores_gemma":[0.9998964,0.00001635025,0.00002925423,0.000008794812,0.00003576737,0.00001344847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005220873,0.00008851582,0.7973779,0.00005978078,0.0001167993,0.0001760552,0.0007377395,0.07780933,0.06150005,0.0005762266,0.00075961,0.06027592],"study_design_scores_gemma":[0.00002701644,0.00004030666,0.9121791,0.000007715988,0.00002594627,0.00005832653,0.0002146553,0.08063526,0.005891225,0.0003108525,0.0005851297,0.00002441917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990282,0.00001832327,0.0003062812,0.000009121684,4.733944e-7,0.000002584844,0.0002525005,0.00003299438,0.0003495075],"genre_scores_gemma":[0.9994889,0.000008813439,0.0003015726,0.000001104984,5.851862e-7,0.00000141215,0.0001305802,0.0000014794,0.00006539005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1467973,"threshold_uncertainty_score":0.2918856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007213839679246114,"score_gpt":0.215858648359443,"score_spread":0.2086448086801969,"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."}}