{"id":"W4320523643","doi":"10.1016/j.amc.2023.127888","title":"Extending the Adapted PageRank Algorithm centrality model for urban street networks using non-local random walks","year":2023,"lang":"en","type":"article","venue":"Applied Mathematics and Computation","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Centrality; PageRank; Jump; Random walk; Computer science; Node (physics); Katz centrality; Intersection (aeronautics); Network science; Theoretical computer science; Graph; Algorithm; Complex network; Mathematics; Betweenness centrality; Geography; Statistics; Cartography","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":[0.001177985,0.0006488066,0.001222499,0.00180112,0.0007436586,0.001751588,0.002565616,0.001510701,0.003113331],"category_scores_gemma":[0.006201222,0.0003909626,0.0009755726,0.002344342,0.0009291588,0.003816141,0.00104834,0.001017376,0.00112354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009549599,"about_ca_system_score_gemma":0.0009096443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00571785,"about_ca_topic_score_gemma":0.009261112,"domain_scores_codex":[0.9986612,0.0005238904,0.00004787941,0.0002897039,0.0003780311,0.00009937947],"domain_scores_gemma":[0.9969537,0.001678371,0.0003003711,0.0003597248,0.0006027044,0.0001051961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006431462,0.0001060692,0.002375271,0.0001632201,0.0001004125,0.0002034005,0.0001594321,0.7840025,0.001713351,0.1576684,0.003274954,0.05016853],"study_design_scores_gemma":[0.000004804479,0.00001377535,0.0001627026,0.000004706971,0.000008616903,0.00003200146,0.000009353774,0.9737994,0.0001292318,0.02516592,0.0006629812,0.000006556282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02408618,0.0002673475,0.9720351,0.0002665961,0.0000734338,0.00006508741,0.0001792609,0.0002520021,0.002775114],"genre_scores_gemma":[0.7668344,0.0008258653,0.2158154,0.0001668505,0.000375913,0.0002429585,0.0006013733,0.000213938,0.01492336],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00571785,"threshold_uncertainty_score":0.01136911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04347540530057762,"score_gpt":0.3148585513550658,"score_spread":0.2713831460544882,"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."}}