{"id":"W4360616065","doi":"10.1080/17538947.2023.2187467","title":"Digital earth: yesterday, today, and tomorrow","year":2023,"lang":"en","type":"article","venue":"International Journal of Digital Earth","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Innovation, Science and Economic Development Canada","keywords":"Digital transformation; Yesterday; Digital Earth; Data science; Computer science; Realization (probability); Management science; Engineering; Geography; World Wide Web; Cartography; Mathematics","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":[0.001022141,0.0004934728,0.0003769441,0.001469158,0.003879557,0.00935753,0.000746184,0.002831125,0.008129198],"category_scores_gemma":[0.002028337,0.0001711376,0.000315024,0.002480125,0.005437683,0.01316625,0.00458525,0.003933017,0.001698324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003772005,"about_ca_system_score_gemma":0.002997234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008988817,"about_ca_topic_score_gemma":0.01700656,"domain_scores_codex":[0.9990789,0.0002056611,0.00004343118,0.0001290674,0.0003293278,0.0002135541],"domain_scores_gemma":[0.9993299,0.0001445112,0.00006740948,0.0000693754,0.0001845707,0.0002042628],"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":[0.00008726574,0.00003079411,0.002406337,0.0007263577,0.00001920355,0.0003214313,0.01052121,0.0002181213,0.0007345965,0.6270202,0.1611861,0.1967284],"study_design_scores_gemma":[0.000001713041,0.00001082096,0.001047672,0.0003572017,0.000004415374,0.0001777109,0.005800033,0.00002758875,0.0001547997,0.021247,0.9711575,0.00001345506],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0281779,0.2388357,0.01023371,0.2004965,0.02134938,0.00006071402,0.001388848,0.0004315319,0.4990258],"genre_scores_gemma":[0.5802131,0.2216177,0.01249158,0.02949523,0.005025934,0.0001065699,0.002177607,0.0003116292,0.1485606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00935753,"threshold_uncertainty_score":0.02736795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01154915638233496,"score_gpt":0.2177140513049441,"score_spread":0.2061648949226092,"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."}}