{"id":"W2114849117","doi":"10.2902/1725-0463.2008.03.art9","title":"Next-Generation Digital Earth: A position paper from the Vespucci Initiative for the Advancement of Geographic Information Science","year":2008,"lang":"en","type":"article","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":213,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Digital Earth; Position (finance); Government (linguistics); Stakeholder; Joint (building); European commission; Geographic information system; Commission; Reflection (computer programming); Position paper; Political science; Geography; Remote sensing; Computer science; Engineering; Business; Public relations; Architectural engineering; World Wide Web; European union","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001214048,0.0001999183,0.0002183337,0.0002799663,0.004269528,0.0003975198,0.0005792292,0.0001418423,0.00001290344],"category_scores_gemma":[0.001131385,0.0001400179,0.0001683676,0.001087352,0.0002799266,0.004600021,0.0001219571,0.0001877251,0.000006443438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002113298,"about_ca_system_score_gemma":0.0006913178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002740408,"about_ca_topic_score_gemma":0.0004969327,"domain_scores_codex":[0.9972906,0.0001606162,0.0006729796,0.0002441623,0.001200782,0.0004308621],"domain_scores_gemma":[0.9968902,0.000610565,0.0005667442,0.0003419406,0.001463103,0.0001273721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007360724,0.0000809467,0.001945497,0.00001356077,0.00009789517,9.800086e-7,0.03514121,0.00011533,0.0007688057,0.958876,0.0001926248,0.002693619],"study_design_scores_gemma":[0.0006551034,0.00005769045,0.03210185,0.0000489752,0.00004140944,0.00003146975,0.01147216,0.0005799413,0.0003669499,0.0003945064,0.9540426,0.0002073575],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5883937,0.001940075,0.08069751,0.1613632,0.005432425,0.008258617,0.0009342843,0.000666528,0.1523137],"genre_scores_gemma":[0.9972548,0.0006070177,0.0006098293,0.0004788174,0.0004458818,0.000400545,0.0001620772,0.000008471089,0.00003251018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9584814,"threshold_uncertainty_score":0.9970268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04525849787990174,"score_gpt":0.2618952635450842,"score_spread":0.2166367656651825,"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."}}