{"id":"W3020026004","doi":"10.3390/rs12091376","title":"Geospatial Assessment of Water-Migration Scenarios in the Context of Sustainable Development Goals (SDGs) 6, 11, and 16","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia; McMaster University; United Nations University Institute for Water, Environment, and Health","funders":"","keywords":"Geospatial analysis; Sustainable development; Urbanization; Nexus (standard); Geography; Environmental planning; Context (archaeology); Environmental resource management; Population; Urban sprawl; Regional science; Environmental science; Remote sensing; Political science; Computer science; Urban planning; Economic growth; Civil engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009113502,0.00007214588,0.0001508417,0.00005846754,0.0001879288,0.00004443405,0.00006077959,0.00005199197,0.000008382117],"category_scores_gemma":[0.0002195269,0.00005496062,0.00002101186,0.000202017,0.00008178298,0.0001412431,0.00002782012,0.00005612923,7.156593e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000180507,"about_ca_system_score_gemma":0.0001899814,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01740209,"about_ca_topic_score_gemma":0.1001801,"domain_scores_codex":[0.9988161,0.0002366935,0.0003010438,0.0001350821,0.0003225439,0.0001885204],"domain_scores_gemma":[0.9994156,0.0001437375,0.0001356479,0.00006798522,0.0002024643,0.00003456508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002885942,0.00003279853,0.002935149,0.00015225,0.00001549664,0.00001134638,0.9142784,0.0002703198,0.02744129,0.003574256,0.00009769824,0.05116211],"study_design_scores_gemma":[0.0007946354,0.0001033695,0.01051992,0.000167211,0.00003292091,0.000001686784,0.8490604,0.1010289,0.02819443,0.0004384783,0.009405985,0.0002520303],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864295,0.00002703316,0.008127404,0.004449098,0.0000321911,0.0004158994,8.066053e-7,0.00001181264,0.0005062671],"genre_scores_gemma":[0.9972128,0.00003533351,0.002442411,0.0001905922,0.0000521411,8.423363e-8,0.00001880517,0.000005653793,0.00004221765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1007586,"threshold_uncertainty_score":0.9891411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06374542324709487,"score_gpt":0.311626660883317,"score_spread":0.2478812376362222,"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."}}