{"id":"W2094863989","doi":"10.4028/www.scientific.net/amm.174-177.2222","title":"Study on Optimization Strategy of Urban Residential Quarter Dealing with the Climate Change in Winter Cities","year":2012,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Environmental Engineering and Cultural Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Human settlement; Climate change; Environmental planning; Quarter (Canadian coin); Urban planning; Business; Environmental resource management; Geography; Environmental science; Civil engineering; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003774454,0.0005949796,0.000720517,0.0004427556,0.0006225944,0.001128979,0.0005758302,0.0005893801,0.003598725],"category_scores_gemma":[0.0005438047,0.0002568834,0.00066529,0.0005601416,0.0002771806,0.0006236079,0.0004592932,0.0002542453,0.0001582476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00071145,"about_ca_system_score_gemma":0.0006678397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008718083,"about_ca_topic_score_gemma":0.005604721,"domain_scores_codex":[0.9997732,0.00007349149,0.000008151513,0.00003622865,0.00003389678,0.00007516078],"domain_scores_gemma":[0.9998628,0.00003982758,0.00002409903,0.00000777171,0.00004139644,0.00002415001],"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":[0.0001267292,0.00007908721,0.003899527,0.0001239171,0.00005817728,0.0002594291,0.0001911611,0.9641291,0.005276392,0.006953539,0.001444308,0.01745856],"study_design_scores_gemma":[0.00001138122,0.0001052707,0.002628886,0.000007649513,0.00003334766,0.00004286762,0.0004002694,0.9924737,0.001066528,0.002011039,0.001209106,0.000009963213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6534504,0.001075184,0.3099161,0.0007274767,0.00009325209,0.0001391412,0.0001444799,0.0002036986,0.03425023],"genre_scores_gemma":[0.9879369,0.000265743,0.008753094,0.00003236286,0.00001191226,0.00003220485,0.00004342693,0.00002176032,0.002902534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008718083,"threshold_uncertainty_score":0.01733464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714611910445382,"score_gpt":0.214218964222562,"score_spread":0.1970728451181082,"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."}}