{"id":"W2529544702","doi":"10.1007/s10479-016-2336-8","title":"An applicable method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Resource-Constrained Project Scheduling","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Calgary","keywords":"Computer science; Schedule; Scheduling (production processes); Operations research; Mathematical optimization; Operating system; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001718978,0.0009802231,0.0009520811,0.0009077127,0.0006289041,0.0007793155,0.001735538,0.0008065707,0.004174363],"category_scores_gemma":[0.005694827,0.0005770156,0.001117356,0.0009234669,0.0005805754,0.001020133,0.001348103,0.001738177,0.0008616146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006329815,"about_ca_system_score_gemma":0.001756751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003978521,"about_ca_topic_score_gemma":0.005609845,"domain_scores_codex":[0.9989836,0.0002570513,0.00006429532,0.0001766162,0.0004154392,0.0001029732],"domain_scores_gemma":[0.9976692,0.001220225,0.0001674289,0.0003456749,0.0005055239,0.00009192079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003263189,0.0002540608,0.0009269846,0.0002777817,0.0001229978,0.0003668834,0.0003223376,0.2682481,0.02867439,0.04080928,0.004428902,0.655242],"study_design_scores_gemma":[0.00004732907,0.00007627529,0.0001860452,0.00001973758,0.00003980732,0.0001255034,0.00003193591,0.9716346,0.005850419,0.01614773,0.005810494,0.00003019177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001799248,0.00002402254,0.9971039,0.00001763418,0.00003889038,0.00006001505,0.0000238166,0.0003527594,0.0005797877],"genre_scores_gemma":[0.04916803,0.00006577246,0.9481149,0.00003654562,0.00003622182,0.0001672076,0.0000852853,0.0002558738,0.002069996],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004174363,"threshold_uncertainty_score":0.01396459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4946935409284301,"score_gpt":0.5864833560107651,"score_spread":0.09178981508233497,"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."}}