{"id":"W4405495768","doi":"10.1007/978-3-031-61503-0_5","title":"Application of Topsis Decision-Making Technique in Selecting a Sustainable Project Financing Model for Infrastructure in China","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"TOPSIS; China; Business; Decision-making models; Decision model; Finance; Computer science; Operations research; Engineering; Geography; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001806662,0.0004013,0.0006549499,0.003696197,0.00004749418,0.0001140564,0.0005208288,0.0004676228,0.00002408261],"category_scores_gemma":[0.001929883,0.0003752244,0.00015415,0.001510072,0.00002593617,0.0002694716,0.0002553203,0.0009511564,0.000001242717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004763452,"about_ca_system_score_gemma":0.0002097765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007804475,"about_ca_topic_score_gemma":0.002237933,"domain_scores_codex":[0.9971206,0.00001060378,0.001140143,0.0007624006,0.0005256076,0.0004406408],"domain_scores_gemma":[0.9978544,0.001205336,0.0003116552,0.0004639322,0.0001446653,0.00001997694],"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":[0.00003761517,0.000004926981,0.0006792236,0.0005466899,0.000008893277,0.000008887404,0.001029005,0.8684828,0.0001360286,0.01290934,0.00002142211,0.1161352],"study_design_scores_gemma":[0.000154768,0.00002002202,0.0001860424,0.001224092,0.000009515609,0.000008558976,0.00002059343,0.752445,0.0001123345,0.2431659,0.002368464,0.000284667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002134343,0.0005214421,0.987351,0.00003515414,0.0001788032,0.001932403,0.0000125028,0.00007254601,0.007761816],"genre_scores_gemma":[0.9636408,0.00004432899,0.034322,0.00001375045,0.00008458729,0.0003411447,0.000006575969,0.00006899846,0.001477829],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9615064,"threshold_uncertainty_score":0.9998699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01411712811264603,"score_gpt":0.2975350364235743,"score_spread":0.2834179083109283,"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."}}