{"id":"W2677624263","doi":"10.1007/s12532-019-00172-4","title":"A rotation-based branch-and-price approach for the nurse scheduling problem","year":2019,"lang":"en","type":"article","venue":"Mathematical Programming Computation","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Group for Research in Decision Analysis; Polytechnique Montréal","funders":"Agence Nationale de la Recherche","keywords":"Theory of computation; Nurse scheduling problem; Embedding; Scheduling (production processes); Time horizon; Computer science; Mathematical optimization; Mathematics; Mathematical economics; Job shop scheduling; Algorithm; Artificial intelligence; Schedule; Flow shop scheduling","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003851781,0.0001586173,0.0002736264,0.0001547373,0.0004079153,0.0006601935,0.0003272981,0.00007972008,0.00003170396],"category_scores_gemma":[0.002586626,0.00009954677,0.0001449862,0.0007105147,0.0001161833,0.0001704416,0.00002500046,0.0001657419,0.0001626943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002758073,"about_ca_system_score_gemma":0.00007676028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004685643,"about_ca_topic_score_gemma":4.405537e-7,"domain_scores_codex":[0.9977126,0.0001200745,0.0006007347,0.0004637601,0.0007703848,0.0003324116],"domain_scores_gemma":[0.9924667,0.006464712,0.0002535549,0.0003237948,0.0003975519,0.00009364764],"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":[0.00006955005,0.0005027994,0.001846114,0.0002843819,0.00007881199,2.95903e-7,0.002353306,0.5921149,0.0001186174,0.08387021,0.0001371901,0.3186238],"study_design_scores_gemma":[0.0005491513,0.00006476489,0.0002981056,0.00003528554,0.00004160931,0.000004281791,0.0007592711,0.9079281,0.00002588293,0.0897793,0.0003883564,0.000125914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03796949,0.0001069283,0.9579964,0.001197266,0.0001086404,0.001616943,0.000002123508,0.0001408391,0.0008613262],"genre_scores_gemma":[0.5531111,1.321097e-7,0.4464511,0.00007646673,0.00003868052,0.0001569257,0.000008814191,0.00001249047,0.0001442791],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5151416,"threshold_uncertainty_score":0.6366261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07469503885769585,"score_gpt":0.3679291525926293,"score_spread":0.2932341137349334,"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."}}