{"id":"W4403920094","doi":"10.1109/sm63044.2024.10733477","title":"Naturalistic Data Analysis: Assessing Factors Impacting E-bike Cyclist Safety on Urban Roads","year":2024,"lang":"en","type":"article","venue":"","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Transport engineering; Computer science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.009274689,0.0002969729,0.0003513882,0.000886314,0.00120327,0.001256544,0.0005202323,0.0004036418,0.001230427],"category_scores_gemma":[0.04463404,0.0002368002,0.000579646,0.0008896709,0.0009296944,0.0007739283,0.0008717293,0.0003867998,0.0002240668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008524521,"about_ca_system_score_gemma":0.001801966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01199623,"about_ca_topic_score_gemma":0.02047571,"domain_scores_codex":[0.9898817,0.007252399,0.0006272409,0.0009409399,0.001038314,0.0002594297],"domain_scores_gemma":[0.9546893,0.02965114,0.007441011,0.003006459,0.004209262,0.00100274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008986228,0.001103529,0.9577732,0.0003704033,0.0003550627,0.0002041451,0.01124271,0.001606751,0.002248196,0.0004851853,0.001116929,0.02259512],"study_design_scores_gemma":[0.00005810573,0.001886716,0.9724822,0.00006751248,0.00009282905,0.0002467528,0.01310922,0.008147212,0.001122089,0.0007207632,0.002017261,0.00004927745],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947845,0.00002891776,0.003448335,0.00006355481,0.000006533384,0.0004361528,0.0004508018,0.00001986925,0.0007612939],"genre_scores_gemma":[0.9918064,0.00003257353,0.006260695,0.00004242466,0.000005014162,0.0009034659,0.0007223751,0.000006809641,0.0002204173],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01199623,"threshold_uncertainty_score":0.04904985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08413262439684419,"score_gpt":0.4136121147348712,"score_spread":0.329479490338027,"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."}}