{"id":"W2605683663","doi":"10.1088/1755-1315/61/1/012114","title":"The application of MATLAB-based analytic hierarchy process in Hainan residential quarter function factor evaluation","year":2017,"lang":"en","type":"article","venue":"IOP Conference Series Earth and Environmental Science","topic":"Evaluation Methods in Various Fields","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Education of Zhejiang Province; Zhejiang University; University of Pittsburgh","keywords":"Analytic hierarchy process; Quarter (Canadian coin); Ranking (information retrieval); Real estate; MATLAB; Factor (programming language); Tourism; Index (typography); Computer science; Function (biology); Investment (military); Econometrics; Software; Residential real estate; Operations research; Environmental economics; Business; Engineering; Geography; Economics; Finance; Artificial intelligence","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":[0.001778445,0.0001242024,0.000121969,0.0000525809,0.000986688,0.000210746,0.000474937,0.00005915094,0.0004568264],"category_scores_gemma":[0.0002219577,0.00009786628,0.00002431952,0.0001425699,0.002450165,0.0009337151,0.0001473465,0.0001260687,0.00002425405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008927614,"about_ca_system_score_gemma":0.00007921935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003123294,"about_ca_topic_score_gemma":0.001710053,"domain_scores_codex":[0.9979829,0.0001268265,0.0002759269,0.0004208341,0.0009250544,0.0002684627],"domain_scores_gemma":[0.9990206,0.00005734745,0.0002764198,0.0005413191,0.00001715178,0.00008712973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002816862,0.0001195044,0.3647228,0.00002768231,0.00000689553,0.000001573081,0.002321647,0.005136989,0.3102254,0.00111473,0.00001584773,0.3160252],"study_design_scores_gemma":[0.0003362636,0.0001444967,0.9054,0.00001107692,0.00001197642,0.000001843614,0.0006498279,0.0531996,0.03710154,0.0028542,0.0001633511,0.0001258391],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944,0.00002229967,0.00298522,0.0004793716,0.00009946726,0.0004511898,0.000005881046,0.00000819806,0.00154835],"genre_scores_gemma":[0.9989476,0.00002655174,0.0008193624,0.00003482424,0.0000123388,0.00005703649,0.000004677551,0.000004662061,0.00009296376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5406771,"threshold_uncertainty_score":0.9027734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02807442961126325,"score_gpt":0.3100562953688927,"score_spread":0.2819818657576294,"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."}}