{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001699362,0.0003913956,0.0001876578,0.002506377,0.000179983,0.0003980584,0.0003029725,0.0001897771,0.000612955],"category_scores_gemma":[0.000217818,0.0001533567,0.0003419096,0.001132189,0.000150403,0.0003401675,0.0002169404,0.0001447076,0.0002352841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002483941,"about_ca_system_score_gemma":0.0003458197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01461342,"about_ca_topic_score_gemma":0.02443858,"domain_scores_codex":[0.9998984,0.000007429404,0.000007156647,0.00002839574,0.00003296931,0.00002553932],"domain_scores_gemma":[0.9998962,0.0000109434,0.00002108164,0.00001023148,0.00004635421,0.00001518816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004664077,0.0004247152,0.2761098,0.0004376177,0.0003118756,0.00123997,0.0006572227,0.05014983,0.2113649,0.001550709,0.009205258,0.4480816],"study_design_scores_gemma":[0.00002129498,0.00006076949,0.5859957,0.00002398004,0.000101363,0.0001892801,0.0004255535,0.3861797,0.02358666,0.0003832864,0.002978159,0.00005424454],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.955382,0.0002445425,0.03774411,0.0000751447,0.00004244368,0.0001244514,0.002472332,0.001041059,0.002873823],"genre_scores_gemma":[0.9585485,0.0001743471,0.03684443,0.00002708322,0.0000327181,0.00006105933,0.003018695,0.00005541788,0.00123777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01461342,"threshold_uncertainty_score":0.02905673,"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."}}