{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001302815,0.00009842702,0.0001826989,0.00004807463,0.001000635,0.0001137559,0.00009905987,0.00007038007,0.000004958428],"category_scores_gemma":[0.00002576565,0.00008071899,0.00006871753,0.0003093734,0.0001401311,0.0000502845,0.00002253343,0.00007612789,0.000001703136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004753409,"about_ca_system_score_gemma":0.00005778357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002521424,"about_ca_topic_score_gemma":0.0003567423,"domain_scores_codex":[0.9990643,0.00003524343,0.000262877,0.0001845803,0.0002197101,0.0002332589],"domain_scores_gemma":[0.9990718,0.0005718044,0.0001195587,0.0001031414,0.00007364654,0.00006000868],"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":[0.00001110091,0.00005128798,0.00001104327,0.0000469332,0.00004267353,2.492595e-7,0.01256846,0.8161661,0.00002587896,0.03346001,0.0001784219,0.1374379],"study_design_scores_gemma":[0.0004186578,0.000004931802,0.00004185516,0.00001550169,0.0000741724,6.973637e-8,0.005590629,0.9546608,0.000006262928,0.0390578,0.0000353714,0.0000938914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02759759,0.00002453427,0.971392,0.0001387266,0.00003825506,0.0005811804,0.000007393183,0.00005761705,0.0001627281],"genre_scores_gemma":[0.9785572,0.00003250232,0.02107937,0.0000552747,0.0001128222,0.00006188549,0.00005954298,0.00001076069,0.00003059251],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9509597,"threshold_uncertainty_score":0.7696179,"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."}}