{"id":"W3143314798","doi":"10.1109/mcomstd.2021.9392785","title":"Guest Editorial: Data Analytics Streamlines Autonomous Driving","year":2021,"lang":"en","type":"editorial","venue":"IEEE Communications Standards Magazine","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Exfo Electro-Optical Engineering (Canada)","funders":"","keywords":"Big data; Computer science; Automation; Augmented reality; Set (abstract data type); Analytics; Human–computer interaction; Key (lock); Virtual reality; Data science; Artificial intelligence; Data mining; Computer security; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.004865741,0.002959404,0.002465381,0.002863757,0.002224078,0.007705349,0.002807762,0.013514,0.01183292],"category_scores_gemma":[0.01387457,0.0008608908,0.001604721,0.001551689,0.002550285,0.004293109,0.001499152,0.01915736,0.01347841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001949491,"about_ca_system_score_gemma":0.002001508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001124118,"about_ca_topic_score_gemma":0.003117435,"domain_scores_codex":[0.9964325,0.0005016004,0.0003976302,0.0004840833,0.001968917,0.0002151299],"domain_scores_gemma":[0.985173,0.005464446,0.000786561,0.0003590253,0.006202445,0.00201464],"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":[0.00002998583,0.00001157128,0.00002931181,0.000139606,0.00001064132,0.00009561284,0.00000933356,0.00003236036,0.00006354949,0.0003642421,0.9929496,0.006264132],"study_design_scores_gemma":[0.00003440112,0.00002707604,0.000186405,0.0002660439,0.00002371624,0.0002005571,0.00002819797,0.0002223839,0.000119227,0.0009557782,0.9979219,0.00001428499],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00006371445,0.00851826,0.0004441172,0.04962934,0.9380375,0.00002535798,0.00009861683,0.0001221174,0.003060905],"genre_scores_gemma":[0.0005803106,0.006910337,0.000194627,0.01901813,0.9620413,0.00002281351,0.00005686624,0.00005639837,0.01111924],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.013514,"threshold_uncertainty_score":0.03958505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02961020465889903,"score_gpt":0.3144424575640681,"score_spread":0.2848322529051691,"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."}}