{"id":"W4400235304","doi":"10.11159/iccste24.160","title":"Comparing the Future Trend of the Number of Road Accidents in Non-Motorized Vehicles Using a Predictive Mathematical Method","year":2024,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Civil, Structural and Transportation Engineering","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Transport engineering; Engineering","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":[0.0001078556,0.0001069134,0.0001424558,0.0000736646,0.00001990966,0.00002446971,0.0002497541,0.00003934841,0.00001042087],"category_scores_gemma":[0.000007757461,0.00006241207,0.00006203457,0.0001659785,0.00003252188,0.0001598343,0.00001717524,0.0001683654,6.971668e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002635608,"about_ca_system_score_gemma":0.000006284681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002097301,"about_ca_topic_score_gemma":0.00001940226,"domain_scores_codex":[0.9993001,0.000002796074,0.0002861969,0.00009645081,0.0002412119,0.0000732984],"domain_scores_gemma":[0.9997957,0.00002475266,0.00006563121,0.00004461484,0.00005571142,0.00001364168],"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":[0.0001817882,0.00005405816,0.06078342,0.003158477,0.0009238452,0.000001678443,0.013383,0.1164606,0.3635919,0.4306601,0.0001285964,0.01067257],"study_design_scores_gemma":[0.000176616,0.000006970684,0.1929611,0.0006533577,0.00003954159,0.000003718559,0.0003936057,0.7921694,0.01201718,0.001498263,0.000016301,0.00006400219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994906,0.00003003558,0.003754494,0.000108367,0.0003739892,0.0001813314,0.00002618993,0.00009617657,0.0005234141],"genre_scores_gemma":[0.9989113,0.00003165552,0.0009864395,0.000003338639,0.00003522768,0.00001195123,0.000002332009,0.000009988924,0.000007746999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6757088,"threshold_uncertainty_score":0.254509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137690064706938,"score_gpt":0.262124614580749,"score_spread":0.2483556081100552,"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."}}