{"id":"W3090616050","doi":"10.1007/s11111-020-00366-2","title":"Comparative assessment of gridded population data sets for complex topography: a study of Southwest China","year":2020,"lang":"en","type":"article","venue":"Population and Environment","topic":"Impact of Light on Environment and Health","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"State Key Laboratory for Environmental Criteria and Risk Assessment; National Natural Science Foundation of China","keywords":"Population; Geography; Data set; Cartography; Scale (ratio); China; Grid; Distribution (mathematics); Spatial ecology; Physical geography; Remote sensing; Statistics; Demography; Ecology; Archaeology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002536165,0.0001602961,0.0003586508,0.00003388892,0.0001216561,0.00000878961,0.000178196,0.00004040636,0.0005477369],"category_scores_gemma":[0.000006595987,0.0001465416,0.00003840521,0.00007937291,0.00007115834,0.0002041238,0.0002271395,0.00006572543,0.000004679459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006666069,"about_ca_system_score_gemma":0.000002598907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001534083,"about_ca_topic_score_gemma":0.0001394503,"domain_scores_codex":[0.9984829,0.00008246829,0.0004788473,0.0003799046,0.0003868969,0.0001889247],"domain_scores_gemma":[0.9991558,0.00003042413,0.0003367295,0.0003251474,0.00000149768,0.0001504431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005373096,0.0004758805,0.9916099,0.00002997338,0.00002659228,1.620082e-7,0.002488899,0.002994732,0.0009257767,0.00004212165,0.00007859015,0.00127367],"study_design_scores_gemma":[0.001095415,0.0007166255,0.9723701,0.000004930088,0.00005699684,2.462645e-7,0.0007353328,0.0244667,0.00001877682,0.000103759,0.0002961138,0.0001350268],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996584,0.00001313288,0.001554203,0.0004638407,0.00002433332,0.001059826,0.0001179498,0.00001196901,0.0001707723],"genre_scores_gemma":[0.99345,0.00002390836,0.00575638,0.00008608615,0.00002090322,0.00001826103,0.0006272406,0.00001115673,0.000006047056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02147196,"threshold_uncertainty_score":0.5997335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1512718935207537,"score_gpt":0.3741127734916245,"score_spread":0.2228408799708709,"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."}}