{"id":"W3004144975","doi":"10.1007/s00453-023-01201-4","title":"Approximations for Throughput Maximization","year":2024,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Las vegas; Combinatorics; Schedule; Approximation algorithm; Mathematics; Computer science; Discrete mathematics; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001673405,0.0000679173,0.00006298818,0.00009955002,0.0001135474,0.0003651502,0.000298615,0.00003804748,0.00003518632],"category_scores_gemma":[0.00003173378,0.00006151625,0.00004917522,0.0004399956,0.0000190815,0.0005649868,0.00006459915,0.00005898292,0.000105045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000261836,"about_ca_system_score_gemma":0.00007232126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002646345,"about_ca_topic_score_gemma":5.4728e-7,"domain_scores_codex":[0.9992943,0.00001953685,0.0001312416,0.0002558056,0.000131892,0.0001672636],"domain_scores_gemma":[0.9995359,0.00009135644,0.00001531547,0.0002231517,0.00008626888,0.00004797806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[6.34921e-7,0.00002455545,0.000001094265,0.00004776617,0.00001593816,0.00000169975,0.0004593848,0.002092552,0.00005682324,0.7926556,0.01108616,0.1935578],"study_design_scores_gemma":[0.00008847741,0.00002509535,0.000004196088,0.00001111844,0.0000023549,0.000004893016,0.000006783788,0.8626434,0.0003237326,0.03587394,0.1009436,0.00007242314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000005513547,0.0001554433,0.9897656,0.005148578,0.0004265096,0.0003203606,0.00001018392,0.0004831024,0.003684646],"genre_scores_gemma":[0.009490076,0.00003137318,0.9866496,0.0003691272,0.0001398776,0.0001478429,0.00004114779,0.00001481884,0.003116177],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8605508,"threshold_uncertainty_score":0.3521152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0185389624597332,"score_gpt":0.2899269528335395,"score_spread":0.2713879903738063,"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."}}