{"id":"W3098440765","doi":"10.1145/3690821","title":"Efficient polynomial-time approximation scheme for the genus of dense graphs","year":2024,"lang":"en","type":"article","venue":"Journal of the ACM","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Genus; Scheme (mathematics); Mathematics; Polynomial-time approximation scheme; Polynomial; Time complexity; Computer science; Combinatorics; Biology; Zoology; Mathematical analysis","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":[0.001649896,0.00007088303,0.0001274109,0.0001512117,0.0001219361,0.00008865543,0.003164719,0.0000275596,0.000005560695],"category_scores_gemma":[0.001051458,0.00003471112,0.0002774117,0.0005324807,0.00009954483,0.000127879,0.0005847013,0.0002095067,0.000007445074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000380486,"about_ca_system_score_gemma":0.0001067859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.734966e-7,"about_ca_topic_score_gemma":2.055729e-7,"domain_scores_codex":[0.9989293,0.00009468754,0.0002962744,0.0001039572,0.0004118537,0.0001639262],"domain_scores_gemma":[0.9976965,0.0008957487,0.0002062685,0.0009715426,0.0001899468,0.00003999353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007293628,0.0004059952,0.0002449602,0.0004242935,0.0009711881,0.00004603759,0.006168453,0.05042082,0.4484954,0.1949753,0.04604993,0.2510682],"study_design_scores_gemma":[0.0007398881,0.0003328341,0.0008748113,0.0003175553,0.00006882723,0.000370473,0.0001064232,0.6822543,0.06357845,0.2436285,0.007552125,0.0001759067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5589879,0.00534329,0.4181069,0.01528355,0.001544896,0.0005764595,0.000007123864,0.00003277585,0.0001170805],"genre_scores_gemma":[0.9212592,0.00003379813,0.07809833,0.00009616578,0.0001608415,0.000008138197,8.236246e-8,0.00001383615,0.0003296343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6318334,"threshold_uncertainty_score":0.5880888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02356914457743608,"score_gpt":0.2985174432274263,"score_spread":0.2749482986499903,"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."}}