{"id":"W2908653200","doi":"10.3390/rs11020105","title":"Investigative Spatial Distribution and Modelling of Existing and Future Urban Land Changes and Its Impact on Urbanization and Economy","year":2019,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":151,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Land cover; Urbanization; Normalized Difference Vegetation Index; Shrub; Vegetation (pathology); Physical geography; Environmental science; Land use; Grassland; Markov chain; Spatial distribution; Geography; Remote sensing; Climate change; Mathematics; Geology; Statistics; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005181106,0.0001666816,0.0001400436,0.001113866,0.0002560267,0.0006617085,0.0003856729,0.0002480768,0.0008854361],"category_scores_gemma":[0.001161249,0.0001983403,0.0004665813,0.001632717,0.0002763367,0.0008929516,0.0003257077,0.0002185653,0.0001568404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001206778,"about_ca_system_score_gemma":0.0008592465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03603329,"about_ca_topic_score_gemma":0.04500161,"domain_scores_codex":[0.9998172,0.00004558915,0.0000130421,0.00004510987,0.00004284497,0.00003635093],"domain_scores_gemma":[0.9996636,0.000130792,0.00007367654,0.0000352614,0.00007898265,0.00001765435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005759933,0.00009189699,0.3798931,0.000111036,0.00007362136,0.0003370706,0.0004787722,0.5658037,0.002221214,0.00779965,0.001250759,0.0418815],"study_design_scores_gemma":[0.000003444208,0.00002445245,0.1122887,0.00002172443,0.00002519595,0.00006595837,0.0006578934,0.8818625,0.0008906553,0.002360184,0.00178406,0.00001517239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769536,0.0001944157,0.01718358,0.0002350842,0.000006408981,0.00003971959,0.001156262,0.0001009795,0.004129993],"genre_scores_gemma":[0.9930339,0.0001941586,0.00552628,0.000007782523,0.000003530798,0.00002286065,0.000571609,0.000009170901,0.0006307052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03603329,"threshold_uncertainty_score":0.07164711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.020188445315955,"score_gpt":0.2204037500344161,"score_spread":0.2002153047184611,"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."}}