{"id":"W2558964015","doi":"10.1061/(asce)co.1943-7862.0001276","title":"Uncertainty-Aware Linear Schedule Optimization: A Space-Time Constraint-Satisfaction Approach","year":2016,"lang":"en","type":"article","venue":"Journal of Construction Engineering and Management","topic":"Resource-Constrained Project Scheduling","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Schedule; Duration (music); Computer science; Mathematical optimization; Workspace; Scheduling (production processes); Constraint satisfaction; Linear programming; Operations research; Industrial engineering; Engineering; Mathematics; Robot; Algorithm; Artificial intelligence","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":[0.001696603,0.001110349,0.001294908,0.001132008,0.0005751331,0.001361116,0.001551675,0.001027559,0.002817862],"category_scores_gemma":[0.002932172,0.000756749,0.001413215,0.001646519,0.0007466524,0.001047317,0.001153377,0.00128401,0.0002849172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001304676,"about_ca_system_score_gemma":0.002329193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01538006,"about_ca_topic_score_gemma":0.009998941,"domain_scores_codex":[0.9988233,0.0004793272,0.00005112165,0.0001540954,0.0003539782,0.0001381396],"domain_scores_gemma":[0.9983276,0.001137218,0.0001505622,0.00005087756,0.0002724975,0.00006121398],"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":[0.00001684934,0.00001642575,0.0001039875,0.00003632113,0.00001773741,0.00003484461,0.00003058128,0.9861712,0.0003221172,0.005118099,0.0002456112,0.007886201],"study_design_scores_gemma":[0.000003468855,0.0000124404,0.00002483453,0.000003156606,0.00000397335,0.000004105033,0.00000806163,0.9976774,0.0001107818,0.001946318,0.0002026057,0.000002852733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005454327,0.0001312385,0.9920214,0.0001053006,0.00001803652,0.00004691579,0.00005688761,0.00008670214,0.00207922],"genre_scores_gemma":[0.5350398,0.0005426313,0.4601886,0.0001362915,0.00009231397,0.0004315495,0.0003484992,0.000121785,0.003098611],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01538006,"threshold_uncertainty_score":0.03058106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02246267624427383,"score_gpt":0.2689762436004997,"score_spread":0.2465135673562258,"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."}}