{"id":"W2392986289","doi":"","title":"The analysis of international green residential district estimate systems——Taking the LEED,Chinese ecological residential technology assessment manual and others for example","year":2013,"lang":"en","type":"article","venue":"Sichuan Building Science","topic":"Environmental Quality and Pollution","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Green building; Constructive; Process (computing); Weighting; Evaluation methods; Architectural engineering; Environmental resource management; Engineering; Computer science; Environmental science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001753514,0.0001218957,0.0001596879,0.0001374168,0.0009849089,0.000234545,0.0008902022,0.00005844462,0.0001601536],"category_scores_gemma":[0.0002521572,0.0000714644,0.00007025883,0.0009527918,0.002178533,0.0004037476,0.0005273509,0.0001198969,0.000008115705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002101266,"about_ca_system_score_gemma":0.00001737241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005180364,"about_ca_topic_score_gemma":0.0008521947,"domain_scores_codex":[0.9982749,0.00008580392,0.0003328149,0.0003996453,0.0005844943,0.0003223797],"domain_scores_gemma":[0.998839,0.0004611483,0.0003188122,0.000306409,0.00001782417,0.00005683431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004666893,0.0001308619,0.7434531,0.00001797825,0.0002822254,0.000002624628,0.000838128,0.03448164,0.1690641,0.03467613,0.0006264483,0.01638012],"study_design_scores_gemma":[0.0001497834,0.00005353254,0.9363872,0.000006802425,0.0000897586,0.000004596863,0.0005328151,0.05969923,0.000495424,0.002060555,0.0004161524,0.0001040857],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886067,0.00004130079,0.008423317,0.001874622,0.0002540339,0.0004057122,0.00001876751,0.00002227417,0.0003532915],"genre_scores_gemma":[0.997911,0.00001663941,0.001802399,0.00004681723,0.00003445475,0.00007028512,0.000003328143,0.00000514434,0.0001098667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1929342,"threshold_uncertainty_score":0.8026896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01502146554590395,"score_gpt":0.323830836557805,"score_spread":0.3088093710119011,"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."}}