{"id":"W4405305553","doi":"10.1109/tvt.2024.3515992","title":"MV-STGHAT: Multi-View Spatial-Temporal Graph Hybrid Attention Network for Decision-Making of Connected and Autonomous Vehicles","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Graph; Graph theory; Artificial intelligence; Theoretical computer science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000239678,0.0003126666,0.0004729012,0.0006917868,0.0002196274,0.00002566263,0.0002313305,0.0005704834,0.0000218979],"category_scores_gemma":[0.00001775849,0.0003242196,0.000209607,0.0006659349,0.0002941752,0.000117394,0.000005669517,0.0005966492,0.00001572703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000805341,"about_ca_system_score_gemma":0.00003893617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001607333,"about_ca_topic_score_gemma":0.0001625369,"domain_scores_codex":[0.9984261,0.00002734941,0.0005486967,0.000461736,0.0001081354,0.0004279968],"domain_scores_gemma":[0.9991705,0.000242999,0.0000652013,0.0004093943,0.00007138154,0.00004049292],"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":[0.00007417414,0.0001347384,0.0002534495,0.0004171872,0.0005615524,0.00006089712,0.00005683757,0.09435228,0.01007608,0.002098866,0.0001719738,0.891742],"study_design_scores_gemma":[0.001156341,0.0005025206,0.0007859739,0.00128978,0.0003709108,0.0002505311,0.0000972166,0.9272585,0.04870186,0.01411201,0.004708945,0.0007654307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3024862,0.002884053,0.6913821,0.000220424,0.0005376105,0.0004572973,0.00007423788,0.001950623,0.000007468599],"genre_scores_gemma":[0.9810881,0.000427117,0.01813418,0.00002573739,0.00002728749,0.0001965108,0.000009598079,0.0000761361,0.00001534282],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8909765,"threshold_uncertainty_score":0.999921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00817217478572224,"score_gpt":0.2336233939782131,"score_spread":0.2254512191924908,"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."}}