{"id":"W2059822862","doi":"10.1061/(asce)me.1943-5479.0000332","title":"Behavioral Economic Concepts for Funding Infrastructure Rehabilitation","year":2014,"lang":"en","type":"article","venue":"Journal of Management in Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Loss aversion; Behavioral economics; Bidding; Economics; Asset (computer security); Public economics; Asset management; Actuarial science; Business; Microeconomics; Marketing; Risk analysis (engineering); Computer science; Finance","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":[],"consensus_categories":[],"category_scores_codex":[0.0003307173,0.0001247236,0.0001919949,0.0003074917,0.00001659772,0.00002940436,0.0001358853,0.00004866821,0.000006752286],"category_scores_gemma":[0.00002332426,0.0001273192,0.00007966787,0.00006661217,0.000007678526,0.0002342545,0.00001715752,0.0001567451,0.000001096175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002964863,"about_ca_system_score_gemma":0.000003938108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.020089e-7,"about_ca_topic_score_gemma":0.000001176461,"domain_scores_codex":[0.9992298,0.000006169743,0.0003789518,0.00007520759,0.00008431791,0.0002255043],"domain_scores_gemma":[0.999702,0.00007074396,0.00006973096,0.00009217353,0.00002322542,0.00004206219],"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":[0.000009786952,0.00000369953,0.001216249,0.0002045766,0.0000302831,0.000003045875,0.0002204572,0.9734479,0.0006910247,0.002239939,0.0005461868,0.02138688],"study_design_scores_gemma":[0.005105116,0.0006966364,0.06716354,0.001077806,0.0001729209,0.00005588923,0.001647734,0.7640198,0.002955553,0.003980014,0.1521085,0.001016442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7776027,0.00008572252,0.2179714,0.00003092867,0.003454543,0.0002166292,0.000001864957,0.000060348,0.0005758833],"genre_scores_gemma":[0.9571171,0.00002495284,0.04236483,0.000006357954,0.0004360134,0.00001104742,0.000001207611,0.00002844643,0.0000100226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.209428,"threshold_uncertainty_score":0.5191928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005159754096955541,"score_gpt":0.2457159915964227,"score_spread":0.2405562374994671,"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."}}