{"id":"W3184356259","doi":"10.1155/2021/5545117","title":"SAVE-T: Safety Analysis Visualization and Evaluation Tool","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Young Scientists Fund; National Natural Science Foundation of China; York University; Natural Science Foundation for Young Scientists of Shanxi Province; New Jersey Turfgrass Association; New York University","keywords":"Visualization; Computer science; Crash; Visual analytics; Data visualization; Analytics; Data science; Transport engineering; Creative visualization; Data mining; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002619962,0.002318668,0.001115136,0.004818719,0.0005602916,0.002659736,0.001875356,0.00115773,0.0266417],"category_scores_gemma":[0.009560171,0.0006529444,0.001216671,0.001737107,0.0003206567,0.002804365,0.002373506,0.001658537,0.005828643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004767276,"about_ca_system_score_gemma":0.001249712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002801646,"about_ca_topic_score_gemma":0.002010657,"domain_scores_codex":[0.9985293,0.0002885529,0.0001970764,0.0001827015,0.0006668307,0.0001355048],"domain_scores_gemma":[0.9945371,0.002696918,0.0003059553,0.0005246555,0.001665282,0.0002700785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001216865,0.0006158231,0.007170699,0.002265909,0.000225253,0.001414489,0.002083422,0.01073815,0.0213017,0.01147167,0.5480644,0.3934316],"study_design_scores_gemma":[0.0009619021,0.0005664867,0.01528431,0.001151839,0.0003547672,0.002235698,0.001495322,0.2777784,0.08448164,0.0307878,0.5841517,0.0007500459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02142507,0.0006597685,0.4948352,0.001179865,0.0004896247,0.001389638,0.03827428,0.4256527,0.01609384],"genre_scores_gemma":[0.2270366,0.001537128,0.6229647,0.001370525,0.0003332073,0.004456499,0.08345754,0.03694588,0.02189781],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0266417,"threshold_uncertainty_score":0.08912534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01612948137569894,"score_gpt":0.3279742931784252,"score_spread":0.3118448118027263,"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."}}