{"id":"W4411309355","doi":"10.1145/3744639","title":"Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly-Linear Time","year":2025,"lang":"en","type":"article","venue":"Journal of the ACM","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Planar; Flow (mathematics); Computer science; Mathematics; Algorithm; Mathematical optimization; Combinatorics; Geometry; Computer graphics (images)","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":[],"consensus_categories":[],"category_scores_codex":[0.0004121393,0.00008359359,0.0001511918,0.0002537491,0.0000669664,0.00006837371,0.00210233,0.00005266275,0.000007833707],"category_scores_gemma":[0.001021462,0.00005770506,0.0000830525,0.0007156635,0.00002436785,0.000302817,0.0002969453,0.0002009932,0.000007333134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009917287,"about_ca_system_score_gemma":0.00008685733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007474257,"about_ca_topic_score_gemma":0.000004919413,"domain_scores_codex":[0.9991081,0.00008014029,0.0003423023,0.0001121111,0.0002275856,0.0001297163],"domain_scores_gemma":[0.998745,0.0001450976,0.0002248584,0.0007218944,0.0001256498,0.00003750204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008400519,0.002141864,0.03976709,0.000191137,0.0006831017,0.0004710309,0.01137173,0.2606066,0.06157712,0.03782848,0.4570701,0.1274517],"study_design_scores_gemma":[0.001706004,0.0003172483,0.03744574,0.0008333187,0.0000570142,0.0004574128,0.00006188687,0.8843277,0.0232042,0.04672701,0.004517911,0.000344611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03142957,0.0001233158,0.9493988,0.01679269,0.001353561,0.0002789905,0.000001631628,0.00007070404,0.0005507621],"genre_scores_gemma":[0.2604195,0.00003302156,0.7364272,0.001284877,0.0002263067,0.00001281251,0.00000150679,0.00001983002,0.001574928],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6237211,"threshold_uncertainty_score":0.3906688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01102814086935181,"score_gpt":0.2602603873843488,"score_spread":0.249232246514997,"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."}}