{"id":"W1937630595","doi":"10.5194/isprsannals-ii-4-w2-55-2015","title":"BUILDING SPATIOTEMPORAL CLOUD PLATFORM FOR SUPPORTING GIS APPLICATION","year":2015,"lang":"en","type":"article","venue":"ISPRS annals of the photogrammetry, remote sensing and spatial information sciences","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute of Steel Construction; George Mason University","keywords":"Geospatial analysis; Cloud computing; Workflow; Computer science; Thematic map; Data science; Geographic information system; Big data; Visualization; Database; Distributed GIS; World Wide Web; Spatial analysis; Spatial database; GIS applications; Data mining; AM/FM/GIS; Remote sensing; Geography; Cartography; Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0007587608,0.0005355183,0.0004203506,0.0009191993,0.00113707,0.001546095,0.001845521,0.0004518685,0.004393127],"category_scores_gemma":[0.001137746,0.0002904744,0.000658048,0.001180175,0.0003627143,0.002552501,0.002424542,0.0007321722,0.001509612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008307481,"about_ca_system_score_gemma":0.002341952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008440721,"about_ca_topic_score_gemma":0.00599754,"domain_scores_codex":[0.9994473,0.0000719539,0.00005531781,0.0001009016,0.0001859481,0.0001386243],"domain_scores_gemma":[0.999294,0.00005750953,0.00004056152,0.00020186,0.0002229778,0.0001830674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002242723,0.001634764,0.0341455,0.001063254,0.0004011809,0.009095112,0.001694561,0.09948597,0.1997901,0.1562558,0.1864593,0.3077318],"study_design_scores_gemma":[0.0002160775,0.0002221583,0.004702806,0.00007827181,0.0001042064,0.0007292797,0.0008729271,0.7941456,0.05586907,0.01843394,0.124527,0.00009875969],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1957662,0.0007670817,0.7416638,0.001744723,0.0007005486,0.001236167,0.003397768,0.02852152,0.02620213],"genre_scores_gemma":[0.6965598,0.0006119746,0.2864182,0.000316546,0.0001388054,0.0004736113,0.007390001,0.0006741769,0.007416852],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008440721,"threshold_uncertainty_score":0.01678318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06572743416780644,"score_gpt":0.3282958276621396,"score_spread":0.2625683934943331,"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."}}