{"id":"W2527340811","doi":"10.1007/s10479-016-2321-2","title":"An integer programming approach to curriculum-based examination timetabling","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Schedule; Computer science; Theory of computation; Curriculum; Set (abstract data type); Integer programming; Integer (computer science); Course (navigation); Operations research; Mathematics education; Programming language; Mathematics; Algorithm; Sociology; Pedagogy","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02111663,0.0001220169,0.0002402785,0.001793091,0.0006395049,0.0005795826,0.001012884,0.00009013369,0.0002362178],"category_scores_gemma":[0.01603946,0.00007422035,0.0001054035,0.003845496,0.0002282148,0.0008450609,0.0001046877,0.0002059146,0.0005595528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000291333,"about_ca_system_score_gemma":0.0003334657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002416355,"about_ca_topic_score_gemma":0.00005989839,"domain_scores_codex":[0.9945573,0.001282978,0.0006584025,0.0006329925,0.002296481,0.0005718025],"domain_scores_gemma":[0.9920013,0.001125743,0.00005128056,0.0009871033,0.00551904,0.0003155292],"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":[0.00004574116,0.003083132,0.003664922,0.00001351414,0.00005435487,0.000002441661,0.001679539,0.07970081,0.04020597,0.04872159,0.006050965,0.8167771],"study_design_scores_gemma":[0.001494673,0.001844631,0.02997372,0.0003160104,0.00002892106,0.00001327583,0.006496466,0.8057801,0.09988887,0.004805661,0.04836996,0.0009877894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5030773,0.0001022467,0.4873479,0.005381157,0.00009694645,0.0006070536,0.00002483343,0.00006512397,0.003297495],"genre_scores_gemma":[0.9359637,0.000006288064,0.06204889,0.00008885819,0.0001037994,0.0001509714,0.00001332153,0.00001464769,0.001609541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8157892,"threshold_uncertainty_score":0.9922488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5537578790127029,"score_gpt":0.568445045148991,"score_spread":0.01468716613628807,"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."}}