{"id":"W4404995844","doi":"10.2139/ssrn.5044048","title":"Cost Overruns of Infrastructure Projects – Distributions, Causes and Remedies","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Engineering Link (Canada)","funders":"","keywords":"Business; Forensic engineering; Risk analysis (engineering); Environmental science; Finance; Engineering","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":[0.004084918,0.0002992381,0.0005235256,0.00334951,0.0006671485,0.002149121,0.0009089845,0.0009959927,0.002902627],"category_scores_gemma":[0.02526811,0.0004057345,0.0004323814,0.003798093,0.001329475,0.002258739,0.001463641,0.001273687,0.0002614704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003049257,"about_ca_system_score_gemma":0.001575293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006708507,"about_ca_topic_score_gemma":0.008155142,"domain_scores_codex":[0.9943772,0.001573741,0.0004737253,0.0005667508,0.002201726,0.0008068789],"domain_scores_gemma":[0.973974,0.008513968,0.0105412,0.001443544,0.00476888,0.0007584223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006484216,0.0003148159,0.4656036,0.0005183649,0.0003136959,0.001491605,0.00161136,0.1020536,0.003080567,0.1211949,0.008081991,0.2950873],"study_design_scores_gemma":[0.00004514651,0.000334387,0.7648545,0.0003494271,0.0001436327,0.001220147,0.004046602,0.08242191,0.002669888,0.1276214,0.01616339,0.000129669],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9645144,0.003795281,0.008094481,0.004710086,0.00005728214,0.0000499998,0.0004568207,0.00008384784,0.01823792],"genre_scores_gemma":[0.997941,0.0004215865,0.0007369419,0.0000427054,0.00003812465,0.000007099086,0.00005981911,0.000009893058,0.0007428181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006708507,"threshold_uncertainty_score":0.02212399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05556754367078169,"score_gpt":0.3589521083122104,"score_spread":0.3033845646414287,"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."}}