{"id":"W2789021035","doi":"10.5383/swes.7.02.002","title":"GIS Based Surveillance of Road Traffic Accidents (RTA) Risk for Rawalpindi City: A Geostatistical Approach","year":2015,"lang":"en","type":"article","venue":"International Journal of Sustainable Water and Environmental Systems","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Geography; Road traffic; Geographic information system; Spatial analysis; Environmental planning; Cartography; Engineering; Remote sensing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001043602,0.0001589619,0.000443425,0.0001711472,0.00004396341,0.00005477235,0.0002081522,0.00006403738,0.00002515751],"category_scores_gemma":[0.0001449772,0.0001154961,0.0001246706,0.00003533264,0.0001224877,0.0002038051,0.0000863379,0.000128272,0.000002647015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003479331,"about_ca_system_score_gemma":0.00008256844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001899378,"about_ca_topic_score_gemma":0.000001511211,"domain_scores_codex":[0.9980237,0.0001099707,0.0006208445,0.0001954117,0.0007528735,0.000297134],"domain_scores_gemma":[0.998955,0.00006424986,0.0003382686,0.0001449213,0.0002167506,0.0002807995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00755623,0.001767959,0.9591378,0.0007852725,0.001560085,0.001083533,0.001538715,0.01421235,0.001112745,0.0001439542,0.004229487,0.006871866],"study_design_scores_gemma":[0.04112197,0.003532232,0.7840422,0.0005042824,0.0006243034,0.002804066,0.02674423,0.0799953,0.001637501,0.0003969775,0.05754431,0.001052641],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883376,0.0005504363,0.009513238,0.0001248242,0.0003122746,0.0004986951,0.0005144529,0.000009030863,0.000139461],"genre_scores_gemma":[0.9981045,0.00005595653,0.0006133383,0.00003535007,0.0002065251,0.00002022574,0.0004666976,0.00002126889,0.0004761544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1750956,"threshold_uncertainty_score":0.4709792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01316919600163665,"score_gpt":0.2514081319092353,"score_spread":0.2382389359075987,"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."}}