{"id":"W2788555957","doi":"10.1609/aaai.v32i1.12076","title":"A Recursive Algorithm to Generate Balanced Weekend Tournaments","year":2018,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quest University Canada","funders":"","keywords":"Tournament; League; Schedule; Corollary; Scheduling (production processes); Computer science; Directed graph; Hamiltonian path; Simple (philosophy); Mathematics; Graph; Mathematical economics; Operations research; Algorithm; Combinatorics; Mathematical optimization","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002116065,0.0002303903,0.0003575459,0.000323254,0.0004903308,0.0004844762,0.002109792,0.0000987287,0.00063579],"category_scores_gemma":[0.00532637,0.0001543261,0.0001645732,0.001920031,0.0004548034,0.0002589521,0.0003347303,0.0002745825,0.002084059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006029255,"about_ca_system_score_gemma":0.0001435432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005400847,"about_ca_topic_score_gemma":0.0000190202,"domain_scores_codex":[0.9965262,0.00004164636,0.0008754834,0.0006986742,0.001350931,0.0005070142],"domain_scores_gemma":[0.9955165,0.0002451575,0.0005198378,0.0004396745,0.003046585,0.0002321884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003269747,0.00040623,0.0007642487,0.000006834377,0.00007353012,0.000001181893,0.005219575,0.0001857049,0.09660148,0.3160953,0.01043232,0.5698866],"study_design_scores_gemma":[0.00004262607,0.0004621072,0.000485155,0.000159422,0.00002268738,0.000005342622,0.001828942,0.02694344,0.6097608,0.3582017,0.001818455,0.0002693022],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8833275,0.00003497329,0.06063426,0.01761896,0.003480935,0.0008904597,0.00006419545,0.0001230823,0.03382564],"genre_scores_gemma":[0.9790224,0.0000101801,0.01737967,0.0006693776,0.0003975545,0.00002435963,3.985726e-7,0.00001460492,0.002481421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5696173,"threshold_uncertainty_score":0.9986929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2290007459228856,"score_gpt":0.4119095838618458,"score_spread":0.1829088379389602,"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."}}