{"id":"W2561173074","doi":"10.1109/iciev.2016.7760006","title":"Application of remote sensing to quantify local warming trends: A review","year":2016,"lang":"en","type":"review","venue":"","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"University of East Anglia; National Oceanic and Atmospheric Administration; University of Calgary; University Grants Committee; National Aeronautics and Space Administration","keywords":"Global warming; Climate change; Remote sensing; Environmental science; Population; Environmental resource management; Computer science; Geography; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003706505,0.0002382687,0.0008895358,0.00007937493,0.00003245313,0.000005471436,0.0001972051,0.0001308138,0.0006711402],"category_scores_gemma":[0.00004172666,0.000155131,0.0002295,0.0005366872,0.00006483757,0.0000647874,0.0001363684,0.00009574443,0.002254938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002705777,"about_ca_system_score_gemma":0.00001894013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003113444,"about_ca_topic_score_gemma":0.00006711378,"domain_scores_codex":[0.998339,0.00009593106,0.0006403822,0.0004444845,0.000274663,0.0002055362],"domain_scores_gemma":[0.9990264,0.00008162865,0.0002660845,0.0005166791,0.000009614276,0.00009966232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[4.112751e-7,0.0000034996,6.85124e-7,0.005221287,0.000006850273,6.967527e-7,0.000009019682,2.41339e-7,0.000008586957,0.00001453989,0.003279955,0.9914542],"study_design_scores_gemma":[0.00002871083,0.00001555172,0.000002778549,0.03807055,0.0001591246,0.00002095252,0.000001399384,0.00009300352,0.00001514453,0.00002462044,0.9613744,0.000193737],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[2.142102e-7,0.7712,0.2215056,0.00009135457,0.00003951497,0.0005559129,0.000008533114,0.0000312132,0.006567657],"genre_scores_gemma":[0.000006108699,0.9875284,0.0105453,0.00016866,0.00004206307,0.00000583778,0.00003185932,0.00002912459,0.001642617],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9912605,"threshold_uncertainty_score":0.9985219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03811340212880017,"score_gpt":0.3273332146314997,"score_spread":0.2892198125026995,"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."}}