{"id":"W4205101105","doi":"10.1002/essoar.10510203.1","title":"Water Observations from Space: accurate maps of surface water through time for the continent of Africa","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Future Earth","funders":"","keywords":"Geospatial analysis; Satellite imagery; Satellite; Scale (ratio); Remote sensing; Surface water; Water resources; Earth observation; Geography; Environmental resource management; Flood myth; Environmental science; Meteorology; Cartography; Engineering","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":[0.000433461,0.0006125873,0.0002328699,0.002294183,0.0002287905,0.000652893,0.0004769999,0.0002749512,0.003034727],"category_scores_gemma":[0.002440427,0.000225739,0.0002575186,0.00351853,0.0001631041,0.001455461,0.0009976423,0.0003574886,0.00120335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003955608,"about_ca_system_score_gemma":0.0007708766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02329759,"about_ca_topic_score_gemma":0.02599867,"domain_scores_codex":[0.9996897,0.00003879355,0.00002680521,0.00007984575,0.0001281181,0.00003679385],"domain_scores_gemma":[0.9995239,0.00006023758,0.0001250518,0.00007229207,0.0001767669,0.00004163814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003095481,0.0001682061,0.1776115,0.001028321,0.0001640486,0.0007051632,0.00227624,0.05802064,0.01687806,0.005101856,0.1053146,0.6324218],"study_design_scores_gemma":[0.0001602751,0.000108321,0.3717213,0.0004368461,0.00009154966,0.0003500459,0.002702484,0.184663,0.01574861,0.006510263,0.4173441,0.0001631579],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4269406,0.002275061,0.1856822,0.00106654,0.0002263953,0.0009641815,0.3487168,0.01010774,0.02402048],"genre_scores_gemma":[0.6484983,0.001608287,0.2366132,0.00008574768,0.00008226558,0.0008955938,0.1058736,0.0009566817,0.005386349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02329759,"threshold_uncertainty_score":0.04632401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07718368187625453,"score_gpt":0.2412738429188836,"score_spread":0.1640901610426291,"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."}}