{"id":"W2899011591","doi":"10.1080/09537287.2018.1535675","title":"Make-or-break during production: shedding light on change-orders, rework and contractors margin in construction","year":2019,"lang":"en","type":"article","venue":"Production Planning & Control","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Australian Research Council","keywords":"Rework; Profit margin; Change order; Margin (machine learning); Operations management; Business; CLARITY; Profit (economics); Total cost; Production (economics); Project management; Marketing; Engineering; Economics; Computer science; Microeconomics; Accounting; Management; Project planning","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":[0.012162,0.0003061605,0.0003134927,0.00113756,0.001392672,0.003051709,0.001023671,0.0007997284,0.001958954],"category_scores_gemma":[0.06018551,0.0002730174,0.0002464748,0.001146986,0.003394015,0.003059383,0.001923926,0.001369128,0.0002680611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004028454,"about_ca_system_score_gemma":0.002565658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008220618,"about_ca_topic_score_gemma":0.01552144,"domain_scores_codex":[0.982869,0.008371592,0.000856348,0.0006885381,0.00595335,0.001261134],"domain_scores_gemma":[0.8985766,0.05840399,0.03132327,0.002583289,0.005620671,0.003492116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009863119,0.0009627027,0.774097,0.000247012,0.00007998737,0.0007030818,0.02537139,0.00823404,0.002294266,0.004684645,0.0008449377,0.1814946],"study_design_scores_gemma":[0.00001451074,0.000637148,0.9628254,0.0001268703,0.00002320884,0.0003156708,0.02550447,0.003871144,0.001118284,0.002769576,0.002739245,0.00005428835],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938422,0.0005411762,0.0011555,0.0005061221,0.000007071197,0.00001889815,0.00001782085,0.00001017217,0.003900867],"genre_scores_gemma":[0.9992748,0.000121115,0.000291985,0.0000197915,0.000006114933,0.000005994772,0.00001091946,0.00000439498,0.0002649086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.012162,"threshold_uncertainty_score":0.06431955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04689761962377002,"score_gpt":0.3208634167498577,"score_spread":0.2739657971260877,"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."}}