{"id":"W4381714871","doi":"10.1201/9781003348030-13","title":"Advancement of conventional cost benefit for selection of truly sustainable infrastructure alternatives","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Selection (genetic algorithm); Risk analysis (engineering); Business; Environmental economics; Environmental planning; Computer science; Environmental science; Economics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000033991,0.0001489506,0.0002493953,0.0001821378,0.00002098259,0.000005013139,0.00009477176,0.0001566796,0.0003861789],"category_scores_gemma":[0.00001143353,0.000145362,0.0001029012,0.00003068444,0.00004924081,0.00004864269,0.00003965459,0.00008841027,0.000001619575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008401342,"about_ca_system_score_gemma":0.00001664047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009252224,"about_ca_topic_score_gemma":0.00001975579,"domain_scores_codex":[0.999384,5.568788e-7,0.000247679,0.000110339,0.000120187,0.0001372101],"domain_scores_gemma":[0.9995738,0.00004811991,0.00009379403,0.0000919939,0.0001805226,0.00001179997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001360342,0.000002411452,0.0000332262,0.000588402,0.0001981961,5.124546e-7,0.0000163186,0.009633865,0.00008877458,0.9817776,0.002152762,0.005494316],"study_design_scores_gemma":[0.0008132003,0.00030806,0.0003910301,0.0002640626,0.00007997421,0.000002569899,0.0007856895,0.004141671,0.01959483,0.3707853,0.602434,0.0003995596],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.005344587,0.001510801,0.1595673,0.0002314707,0.002469943,0.004479866,0.001424971,0.002422959,0.8225481],"genre_scores_gemma":[0.03156562,0.001420685,0.003186302,0.000005650084,0.000107314,0.0001181737,0.0001939395,0.00009340608,0.9633089],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6109923,"threshold_uncertainty_score":0.5927691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01137197068783097,"score_gpt":0.2230185654618008,"score_spread":0.2116465947739699,"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."}}