{"id":"W3204523649","doi":"10.1016/j.asoc.2021.107932","title":"Estimating long-term impacts of tunnel infrastructure development on urban sustainability using granular computing","year":2021,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Underground infrastructure and sustainability","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Nanyang Technological University; Ministry of Education - Singapore","keywords":"Weighting; Sustainability; Analytic hierarchy process; Computer science; Process (computing); Sustainable development; Term (time); Environmental economics; Risk analysis (engineering); Operations research; Business; Engineering; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008877462,0.0005013649,0.0004283205,0.0009146925,0.0004118385,0.001523918,0.0004964074,0.0008310348,0.0008518058],"category_scores_gemma":[0.004421155,0.0003063868,0.0006813075,0.001527249,0.000703396,0.00174166,0.0009929234,0.0007896902,0.0001105669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001292289,"about_ca_system_score_gemma":0.0007643831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01972089,"about_ca_topic_score_gemma":0.01808574,"domain_scores_codex":[0.9996824,0.00008210326,0.00001870555,0.00005197245,0.00007190422,0.00009298409],"domain_scores_gemma":[0.9976904,0.00149362,0.0002387378,0.000217518,0.0001867956,0.0001728447],"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":[0.0001593406,0.0001040123,0.03830725,0.00004264197,0.00008390463,0.0001292249,0.00003205685,0.9488402,0.001084403,0.001823131,0.0001908829,0.009203036],"study_design_scores_gemma":[0.000004707159,0.00004593243,0.01476817,0.000007181053,0.00002488592,0.00001641369,0.00009102239,0.9819125,0.0006122104,0.002391219,0.0001164755,0.00000926653],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879194,0.0001218248,0.01001807,0.0001304942,0.00001996521,0.00001697254,0.0002992587,0.00007720833,0.001396768],"genre_scores_gemma":[0.9987662,0.0000336443,0.000988332,0.000004870989,0.000002827076,0.000004910723,0.00008749575,0.000003789968,0.0001078713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01972089,"threshold_uncertainty_score":0.03921217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006499957272371633,"score_gpt":0.2322602240596463,"score_spread":0.2257602667872746,"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."}}