{"id":"W4416744700","doi":"10.5753/webmedia.2025.15492","title":"Where Next? A Behavioral and Explainable Framework for City and Neighborhood Recommendation","year":2025,"lang":"","type":"article","venue":"","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Tourism; Recommender system; Work (physics); Through-the-lens metering; Urban computing","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001125022,0.0001939137,0.0003224269,0.0001398208,0.001902066,0.000705853,0.000142481,0.0003334234,0.003304879],"category_scores_gemma":[0.0003266828,0.0002037712,0.0001071797,0.000651833,0.0003853097,0.0006211136,0.00007790672,0.0002193507,0.000003680237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001318612,"about_ca_system_score_gemma":0.0002877942,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007679115,"about_ca_topic_score_gemma":0.02502848,"domain_scores_codex":[0.9982712,0.0002332838,0.0004006915,0.0005759168,0.0001446083,0.0003742815],"domain_scores_gemma":[0.9984997,0.0007762564,0.0001244193,0.0002130473,0.0002236471,0.0001629591],"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":[0.00007577839,0.0005092429,0.03668771,0.0003022574,0.0001087588,3.220339e-7,0.01266656,0.000004685213,0.00001243463,0.4196971,0.001537899,0.5283973],"study_design_scores_gemma":[0.001637135,0.0005877572,0.009151326,0.0005153656,0.001299247,3.458291e-7,0.1845066,0.02491998,0.0001184751,0.6961839,0.08016762,0.0009121741],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2395854,0.00394556,0.670137,0.06088074,0.0007624093,0.002669204,0.00006708962,0.0001487763,0.02180378],"genre_scores_gemma":[0.9913093,0.001479829,0.002469685,0.0006128175,0.0001262052,0.0001221503,0.00002445535,0.000007216111,0.003848294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7517239,"threshold_uncertainty_score":0.9993973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0420744495396925,"score_gpt":0.3649248452914126,"score_spread":0.32285039575172,"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."}}