{"id":"W4385796000","doi":"10.3390/rs15164006","title":"Automatic Detection and Dynamic Analysis of Urban Heat Islands Based on Landsat Images","year":2023,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"Urban heat island; Impervious surface; Normalized Difference Vegetation Index; Environmental science; Spatial variability; Vegetation (pathology); Physical geography; Urban climate; Population; Urbanization; Remote sensing; Intensity (physics); Climatology; Climate change; Meteorology; Geography; Geology","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":[0.0001784269,0.00008164615,0.0001508819,0.000221332,0.0000723683,0.00001539402,0.00002622875,0.00004210017,0.00004016068],"category_scores_gemma":[0.00003799315,0.00007374036,0.00005315057,0.0009191677,0.00004927843,0.00005105932,0.00002232928,0.00005220663,0.00003231419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008530233,"about_ca_system_score_gemma":0.000003130044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002711791,"about_ca_topic_score_gemma":0.0002904107,"domain_scores_codex":[0.9993061,0.0000517345,0.0001359817,0.0001875692,0.0001823824,0.0001361741],"domain_scores_gemma":[0.9996601,0.00009913166,0.00003519193,0.0001639513,0.000005065036,0.00003653968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000281063,0.00001704882,0.02653885,0.00005183625,0.0001243647,0.00002362483,0.001055974,0.03291288,0.575367,3.200349e-7,0.0002547652,0.3636252],"study_design_scores_gemma":[0.0001288519,0.00003269732,0.1679293,0.00002228738,0.0001244662,0.000001983775,0.00002965481,0.8236489,0.007975232,0.00002666579,0.00001596657,0.00006394124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917989,0.0000062494,0.006900267,0.00007722494,0.00004048581,0.00007750192,0.000004608061,0.0000905969,0.001004157],"genre_scores_gemma":[0.998895,0.000006477632,0.0009088129,0.00004369481,0.000008312712,1.745276e-8,0.00001993307,0.000009312673,0.0001084576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7907361,"threshold_uncertainty_score":0.3007045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006106444222489963,"score_gpt":0.2186514458033783,"score_spread":0.2125450015808883,"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."}}