{"id":"W4389486639","doi":"10.1007/978-3-031-49190-0_27","title":"Delaying Decisions and Reservation Costs","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Reservation; Upper and lower bounds; Vertex cover; Competitive analysis; Vertex (graph theory); Edge cover; Computer science; Graph; Set (abstract data type); Online algorithm; Mathematical optimization; Combinatorics; Mathematics; Algorithm; Theoretical computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001180744,0.0002687186,0.0002700747,0.0009326952,0.0003579099,0.0007654999,0.001734926,0.000208758,0.000008820241],"category_scores_gemma":[0.0003945596,0.000247756,0.00004746266,0.0009169529,0.0003471274,0.0007194909,0.001696369,0.0005445209,0.00006173222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001813972,"about_ca_system_score_gemma":0.0003285736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002150504,"about_ca_topic_score_gemma":0.0001066943,"domain_scores_codex":[0.9971744,0.00003389326,0.0003744125,0.001068378,0.0008958843,0.0004530295],"domain_scores_gemma":[0.9975631,0.0009722482,0.0001380646,0.0008443929,0.0002990378,0.0001832034],"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":[0.000002302909,0.000008674077,0.00008029215,0.00001200911,0.00000513546,0.00004608834,0.0005174201,0.04964706,0.00004066704,0.09055675,0.00008362593,0.859],"study_design_scores_gemma":[0.00015119,0.00006453144,0.0002042142,0.0003100771,0.000001747598,0.00001900635,1.466049e-7,0.840537,0.00004928545,0.1576055,0.0007739762,0.0002833649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00004181225,0.0001218391,0.9935401,0.001929848,0.0007704581,0.0003121896,0.000002731814,0.0002191921,0.003061838],"genre_scores_gemma":[0.02398101,0.0006111394,0.9707063,0.002235222,0.0002403501,0.00001685159,0.00001340651,0.00005448611,0.002141258],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8587166,"threshold_uncertainty_score":0.9999975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0560672355227835,"score_gpt":0.2952207652891007,"score_spread":0.2391535297663172,"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."}}