{"id":"W2312521449","doi":"10.1061/41002(328)41","title":"A Model to Predict the Impact of Excusable and Non-Excusable Delay on Selected Construction Projects","year":2008,"lang":"en","type":"article","venue":"","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Damages; Postponement; Pre-construction services; Construction management; Schedule; Process (computing); Quality (philosophy); Business; Project planning; Project management; Risk analysis (engineering); Operations management; Engineering; Computer science; Civil engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001438993,0.001492554,0.000735955,0.001561001,0.0007456359,0.002251572,0.001377014,0.002133862,0.008774496],"category_scores_gemma":[0.003556877,0.00068628,0.001023291,0.0009299912,0.0004590363,0.001117694,0.0006767159,0.001745765,0.001134816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002516367,"about_ca_system_score_gemma":0.002056174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07425325,"about_ca_topic_score_gemma":0.03053565,"domain_scores_codex":[0.9996662,0.00006433226,0.00001940175,0.00007941974,0.00005088586,0.0001197481],"domain_scores_gemma":[0.9973952,0.001568184,0.000275314,0.0000548915,0.0004983794,0.000207966],"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":[0.00009549665,0.000074807,0.006153055,0.00001992989,0.0000159606,0.00007279003,0.00001220012,0.9904518,0.0002590628,0.0004590913,0.0005294101,0.001856427],"study_design_scores_gemma":[0.00001382371,0.00003811927,0.001057911,0.000004277728,0.00001046799,0.000008720019,0.00001455895,0.9983628,0.00008679932,0.0002555489,0.0001413872,0.00000550763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9272273,0.0004988374,0.05324909,0.001018518,0.0001595612,0.0002320684,0.005162972,0.001318845,0.01113264],"genre_scores_gemma":[0.985961,0.0002248373,0.005516805,0.00004961804,0.00001502791,0.0001762407,0.001832161,0.00004413057,0.006180226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07425325,"threshold_uncertainty_score":0.1476421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09386223567393061,"score_gpt":0.3484582378382545,"score_spread":0.2545960021643239,"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."}}