{"id":"W4296957141","doi":"10.4230/lipics.icalp.2023.15","title":"Improved Approximation Algorithms by Generalizing the Primal-Dual Method Beyond Uncrossable Functions","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Office of Naval Research; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; European Commission","keywords":"Approximation algorithm; Mathematics; Dual (grammatical number); Discrete mathematics; Function (biology); Combinatorics; Algorithm; Graph; Class (philosophy); Computer science; Artificial intelligence","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001022215,0.0004237754,0.0003679456,0.0002404376,0.001482139,0.0004866971,0.002535366,0.0002246586,0.0001886156],"category_scores_gemma":[0.00003226648,0.0004205002,0.0003647543,0.001329095,0.0001941674,0.0005848512,0.00469727,0.001276717,0.00001948931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003590651,"about_ca_system_score_gemma":0.0002902289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007765586,"about_ca_topic_score_gemma":0.00003878969,"domain_scores_codex":[0.9969155,0.000509964,0.0003223694,0.001478264,0.0002324304,0.0005414789],"domain_scores_gemma":[0.9972454,0.0002627513,0.0003914599,0.001775096,0.0001776138,0.0001476748],"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":[0.00004912971,0.0005071164,0.00028469,0.0001251379,0.0005673805,0.0001061438,0.001712567,0.4297632,0.001242004,0.5295532,0.01193415,0.02415521],"study_design_scores_gemma":[0.0004029586,0.00006563777,0.00004944174,0.00001204613,0.00008526817,0.00001205356,0.0003138949,0.927448,0.0003485371,0.05898937,0.01176371,0.0005091025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006367459,0.0002017915,0.9874662,0.0004425391,0.001650789,0.0005879917,0.000177124,0.0004057506,0.002700363],"genre_scores_gemma":[0.4551735,0.0004746829,0.5071234,0.001787752,0.0009210079,0.00009774035,0.001159631,0.0001659469,0.03309644],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4976848,"threshold_uncertainty_score":0.9998247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06882819582855235,"score_gpt":0.218856385626541,"score_spread":0.1500281897979887,"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."}}