{"id":"W2808727532","doi":"","title":"Pre-processing Road Networks for Graph Partitioning Using Edge-Betweenness Centrality","year":2017,"lang":"en","type":"dissertation","venue":"Utrecht University Repository (Utrecht University)","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Betweenness centrality; Centrality; Computer science; Enhanced Data Rates for GSM Evolution; Graph; Theoretical computer science; Artificial intelligence; Mathematics; Combinatorics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006470645,0.0009338412,0.0008929116,0.002015564,0.001090083,0.001533339,0.001561311,0.0007995471,0.005949066],"category_scores_gemma":[0.004762042,0.0005583504,0.0008535465,0.001963995,0.0004667573,0.001965748,0.001212751,0.001338503,0.001776637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007982753,"about_ca_system_score_gemma":0.001331467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006138401,"about_ca_topic_score_gemma":0.01579434,"domain_scores_codex":[0.9991859,0.0001438753,0.00004358692,0.0002037478,0.0003113397,0.0001115519],"domain_scores_gemma":[0.9979672,0.0007185362,0.0001711534,0.0004527056,0.0006051039,0.00008525992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000208243,0.000230885,0.004771912,0.0004942797,0.0001430261,0.0003381813,0.0008600822,0.3607475,0.04883531,0.04688535,0.01332796,0.5231572],"study_design_scores_gemma":[0.00003817964,0.0001288461,0.002106481,0.00004516794,0.00004964646,0.0002061389,0.0004564845,0.9100365,0.02777306,0.04139866,0.01771781,0.00004307333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01916844,0.0001116325,0.9761235,0.0001253046,0.00004352955,0.000114839,0.0002141784,0.001175221,0.002923255],"genre_scores_gemma":[0.1357682,0.0001085296,0.8600842,0.00006390163,0.00002806029,0.0001774981,0.001234246,0.0004530378,0.002082313],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006138401,"threshold_uncertainty_score":0.01990163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751283936314172,"score_gpt":0.2296191157800906,"score_spread":0.2121062764169489,"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."}}