{"id":"W4366808596","doi":"10.5267/j.jpm.2023.4.001","title":"The time-cost trade-off problem and its extensions: A state-of-the-art survey and outlook","year":2023,"lang":"en","type":"article","venue":"Journal of Project Management","topic":"BIM and Construction Integration","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Heuristics; Computer science; Probabilistic logic; Operations research; Variety (cybernetics); Range (aeronautics); Scheduling (production processes); Table (database); Mathematical optimization; Total cost; Industrial engineering; Management science; Data mining; Mathematics; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006385877,0.00007166064,0.00009999923,0.0001083936,0.00008306457,0.0000478141,0.00008272546,0.00001779963,0.000003608186],"category_scores_gemma":[0.0000210789,0.00004099053,0.00003372587,0.0002420435,0.0000266817,0.00009592901,0.00003797204,0.0001147298,0.000005956626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001947501,"about_ca_system_score_gemma":0.00001337334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002494043,"about_ca_topic_score_gemma":0.0000273908,"domain_scores_codex":[0.9993464,0.00005952122,0.0002696369,0.00005702738,0.0001664477,0.0001009844],"domain_scores_gemma":[0.9996978,0.00005990731,0.0000955537,0.00007619973,0.00004849726,0.00002202203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001253469,0.00004326134,0.003188668,0.0004341081,0.0006903164,0.00002579066,0.001460225,0.002685361,0.001606467,0.002453172,0.1803445,0.8069428],"study_design_scores_gemma":[0.003027362,0.0004574998,0.4096116,0.0009636803,0.0003233727,0.0003882646,0.002086537,0.1044154,0.002197417,0.005686934,0.4701971,0.0006448002],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9622899,0.009748485,0.002449304,0.004307978,0.002936764,0.004027179,0.00006055488,0.0002514001,0.01392839],"genre_scores_gemma":[0.9779264,0.01171215,0.0007856037,0.00008062689,0.00009038077,0.00005414795,0.000004177507,0.00004299837,0.009303512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.806298,"threshold_uncertainty_score":0.1671545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01610673164580742,"score_gpt":0.2365922708587847,"score_spread":0.2204855392129773,"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."}}