{"id":"W2966932193","doi":"10.1109/icra.2019.8794341","title":"IceVisionSet: lossless video dataset collected on Russian winter roads with traffic sign annotations","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research","keywords":"Computer science; Traffic sign; Robustness (evolution); License; Annotation; Artificial intelligence; Python (programming language); Computer vision; Sign (mathematics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0004243815,0.001665126,0.001001589,0.002347909,0.0007072325,0.0009232611,0.001244775,0.001094473,0.004669316],"category_scores_gemma":[0.001027347,0.0002657297,0.0006680915,0.002018115,0.0004741611,0.0007786864,0.0009074554,0.0008889096,0.007129096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007372705,"about_ca_system_score_gemma":0.00100513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02387316,"about_ca_topic_score_gemma":0.05032037,"domain_scores_codex":[0.9992775,0.00006411918,0.00005929371,0.0002391743,0.0002292339,0.0001306823],"domain_scores_gemma":[0.9994996,0.00004302423,0.00004625984,0.0001595031,0.0002022897,0.00004937944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001448991,0.0009352488,0.02016754,0.002776255,0.0004135292,0.001651814,0.000379084,0.009215037,0.0316858,0.001086845,0.7750226,0.1552173],"study_design_scores_gemma":[0.0003821406,0.0008028032,0.2330081,0.001129161,0.0004013367,0.003751393,0.001617543,0.06311835,0.04338418,0.002427453,0.6496277,0.0003498255],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1518316,0.00247005,0.01059152,0.0002668775,0.0008287504,0.0005171721,0.8056166,0.01323042,0.01464701],"genre_scores_gemma":[0.05172672,0.0003513636,0.006182493,0.00005375925,0.00005323143,0.0001516191,0.9387994,0.0002885149,0.002392921],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02387316,"threshold_uncertainty_score":0.04746836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01216101331165788,"score_gpt":0.2581023391743069,"score_spread":0.245941325862649,"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."}}