{"id":"W4399144556","doi":"10.1109/vrw62533.2024.00258","title":"Prototyping Autonomous Vehicle Lane Detection for Snow in VR","year":2024,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de Recherche du Québec-Société et Culture; Canada Research Chairs","keywords":"Autopilot; Computer science; Snow; Feature (linguistics); Virtual reality; Real-time computing; Simulation; Artificial intelligence; Engineering; Aerospace engineering; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000132447,0.00008761745,0.00009556195,0.0001288334,0.00003307963,0.00001884933,0.00006793956,0.0001466416,0.00003985561],"category_scores_gemma":[0.00001189362,0.00008607624,0.00003558118,0.0001700416,0.00001562159,0.00009756391,0.00001187835,0.0001909641,0.00007895874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001082689,"about_ca_system_score_gemma":0.00001428059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001571081,"about_ca_topic_score_gemma":0.000185886,"domain_scores_codex":[0.9994762,0.000004897683,0.000146181,0.0001446325,0.00002788281,0.0002001917],"domain_scores_gemma":[0.9998143,0.00005136573,0.000004796153,0.0001043885,0.00000644773,0.00001868223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001773991,0.00001607172,0.0001935829,0.0002657395,0.00003576479,0.00001554453,0.0002462461,0.004834331,0.0160489,0.01051082,0.0001427372,0.9676725],"study_design_scores_gemma":[0.0002242159,0.000059229,0.001300788,0.00005412523,0.000006744055,0.00001267043,0.00004362375,0.8689478,0.08181894,0.004018075,0.04332768,0.0001861235],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5729513,0.001700351,0.3848032,0.0007020102,0.001019874,0.002425283,0.00001293616,0.01074958,0.02563548],"genre_scores_gemma":[0.9980603,0.00001716407,0.001139805,0.00001905578,0.00004504827,0.0003111057,0.000002978148,0.00002667912,0.0003778461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9674864,"threshold_uncertainty_score":0.3510087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007627342414749654,"score_gpt":0.2195700982155186,"score_spread":0.211942755800769,"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."}}