{"id":"W25572007","doi":"10.1007/978-3-642-22922-0_3","title":"An Ontology-Based Traffic Accident Risk Mapping Framework","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Ontology; Cluster analysis; Traffic accident; Accident (philosophy); Domain (mathematical analysis); Data mining; Point (geometry); Information retrieval; Transport engineering; Artificial intelligence","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":[0.001874616,0.0008747606,0.0008772354,0.003534546,0.001208561,0.003943974,0.002286087,0.001097959,0.003976781],"category_scores_gemma":[0.002470327,0.0005692388,0.002509817,0.003433226,0.0006901523,0.003919374,0.002894786,0.00157543,0.001340634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001491244,"about_ca_system_score_gemma":0.003512945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01764074,"about_ca_topic_score_gemma":0.02095132,"domain_scores_codex":[0.9987239,0.0002157896,0.0002153055,0.0002295235,0.0005185901,0.00009681689],"domain_scores_gemma":[0.9993256,0.000178184,0.000071968,0.0001250924,0.0002270381,0.00007208862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008374704,0.0003934168,0.002388011,0.0006643336,0.0003415953,0.0008622154,0.001383306,0.09684814,0.005864711,0.6277159,0.01966544,0.2437892],"study_design_scores_gemma":[0.00003503609,0.00004885287,0.001627346,0.0003688764,0.0003140329,0.0006198089,0.0007271567,0.3622782,0.004028893,0.4199847,0.2098553,0.0001117162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004140833,0.0002936023,0.9821681,0.0003992149,0.00007377561,0.0002277284,0.001888839,0.002520302,0.008287722],"genre_scores_gemma":[0.07943863,0.0008962499,0.9078457,0.0002102795,0.00004358999,0.0004484537,0.005876868,0.0003598456,0.004880384],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01764074,"threshold_uncertainty_score":0.03507614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02410604625262261,"score_gpt":0.2502911648562512,"score_spread":0.2261851186036286,"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."}}