{"id":"W4400325795","doi":"10.4230/lipics.esa.2024.24","title":"A Parameterized Algorithm for Vertex and Edge Connectivity of Embedded Graphs","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Parameterized complexity; Vertex (graph theory); Enhanced Data Rates for GSM Evolution; Algorithm; Combinatorics; Computer science; Mathematics; Graph; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001001811,0.002130705,0.001696532,0.002112171,0.001403552,0.003421784,0.005012248,0.002379981,0.01298981],"category_scores_gemma":[0.0107331,0.001245067,0.001873881,0.004035354,0.00141811,0.008654858,0.004582146,0.002547324,0.002868927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00286942,"about_ca_system_score_gemma":0.002709495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004669781,"about_ca_topic_score_gemma":0.006685311,"domain_scores_codex":[0.9973911,0.0003415398,0.000190788,0.001143791,0.0006396205,0.000293031],"domain_scores_gemma":[0.9938553,0.002414909,0.0005122765,0.002348653,0.0005942339,0.0002745234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007440298,0.0005576574,0.003402378,0.0007018219,0.0002267033,0.0004328548,0.0006531407,0.3097201,0.01822493,0.1017087,0.02571735,0.5379103],"study_design_scores_gemma":[0.0002103387,0.0001354131,0.0006961655,0.00006315868,0.00007207076,0.0002890235,0.0002130459,0.8120711,0.007187905,0.1680513,0.01095397,0.00005638231],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04224031,0.0003751469,0.9392683,0.0005061348,0.00008397228,0.0004132969,0.001731504,0.008280199,0.007101197],"genre_scores_gemma":[0.2472744,0.0002982298,0.7379174,0.000199031,0.00008128904,0.000539593,0.006682663,0.001575537,0.005431791],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01298981,"threshold_uncertainty_score":0.0434553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05738119772931273,"score_gpt":0.2018477497665598,"score_spread":0.1444665520372471,"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."}}