{"id":"W4417273532","doi":"10.1186/s40163-026-00277-x","title":"Opportunity in Transit: Bus Stop Crowding and Crime","year":2025,"lang":"en","type":"article","venue":"Crime Science","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Agencia Nacional de Investigación y Desarrollo","keywords":"Crowding; Bridging (networking); Crowding out; Property crime; Metropolitan area; Public transport; Estimator; Crowds","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005128495,0.0001872662,0.0001988607,0.0009289622,0.0004531583,0.001093866,0.0002723911,0.0002918836,0.002618408],"category_scores_gemma":[0.003091787,0.00009048259,0.0003184167,0.001050273,0.001183983,0.0007019386,0.001319265,0.0005725591,0.00009748226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001057584,"about_ca_system_score_gemma":0.0006893083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01562718,"about_ca_topic_score_gemma":0.02390405,"domain_scores_codex":[0.9995577,0.0002045132,0.00002086968,0.00007351791,0.00006826167,0.00007509687],"domain_scores_gemma":[0.9983959,0.0005832067,0.0005870191,0.0000684144,0.0001433943,0.000222145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002293263,0.000148846,0.8758538,0.0001543302,0.0001874493,0.0002554877,0.002191414,0.009163998,0.0005837159,0.0579267,0.001254145,0.05205072],"study_design_scores_gemma":[0.000005946044,0.0002112827,0.951939,0.0001247673,0.00007813286,0.0001860806,0.004462311,0.01312392,0.0003743459,0.02110934,0.008354479,0.00003046057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9805162,0.001809026,0.007427507,0.001824414,0.00005712747,0.00002239406,0.0003313549,0.0000116213,0.008000473],"genre_scores_gemma":[0.998515,0.0002832684,0.000522795,0.00002469269,0.00002973528,0.000007080931,0.00005568384,0.000002050416,0.0005596498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01562718,"threshold_uncertainty_score":0.03107244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07666965051367815,"score_gpt":0.4181926620594517,"score_spread":0.3415230115457736,"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."}}