{"id":"W4416944391","doi":"10.1016/j.jag.2025.104999","title":"High-resolution local climate zone mapping via deep mixed-scene decomposition of remote sensing imagery","year":2025,"lang":"en","type":"article","venue":"International Journal of Applied Earth Observation and Geoinformation","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China; Ministry of Natural Resources of the People's Republic of China; Ministry of Natural Resources","keywords":"Robustness (evolution); Fuse (electrical); Image fusion; Dual (grammatical number); Deep learning; Boosting (machine learning); Fusion","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":[0.0003063722,0.0008719163,0.0003652577,0.001544366,0.000200214,0.0005267049,0.0006682386,0.0004043142,0.001159888],"category_scores_gemma":[0.0005079236,0.0002421705,0.0007321642,0.001144799,0.000248506,0.0006425251,0.00083607,0.0006625711,0.0006542478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003523539,"about_ca_system_score_gemma":0.000533114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01042664,"about_ca_topic_score_gemma":0.01961094,"domain_scores_codex":[0.9998061,0.00002907629,0.000005660436,0.00007007409,0.00004811141,0.00004105113],"domain_scores_gemma":[0.9998932,0.00001491391,0.00001190138,0.00002965701,0.00003514128,0.00001514741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006748597,0.0005453058,0.0219424,0.0003880473,0.0004416573,0.00048639,0.0002846961,0.3167322,0.09354945,0.003950992,0.02118202,0.539822],"study_design_scores_gemma":[0.00004180253,0.00004414672,0.01454464,0.00001840641,0.00005606701,0.00007125024,0.0001119862,0.9641833,0.01350073,0.002431165,0.00496846,0.00002801989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6345543,0.001083996,0.3360109,0.0007410901,0.0002591755,0.000166436,0.009415387,0.009358903,0.008409785],"genre_scores_gemma":[0.8508498,0.0002714355,0.1304453,0.0001458601,0.00007279243,0.0000758813,0.01551627,0.0002738416,0.002348797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01042664,"threshold_uncertainty_score":0.02073193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006853866621320828,"score_gpt":0.2143389889272221,"score_spread":0.2074851223059012,"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."}}