{"id":"W3045642713","doi":"10.1609/aaai.v35i10.17114","title":"FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Architecture; Graph; Data mining; Key (lock); Artificial intelligence; Theoretical computer science; Distributed computing; Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.0002287363,0.0002367885,0.0002573566,0.0001497297,0.0001434617,0.0001171909,0.0004333748,0.0001116855,0.00005787424],"category_scores_gemma":[0.0002949187,0.0002042471,0.0001574846,0.0005661488,0.0001236482,0.0001246604,0.00007063956,0.000279938,0.000008777488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003576751,"about_ca_system_score_gemma":0.00004067864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004854075,"about_ca_topic_score_gemma":0.00008618015,"domain_scores_codex":[0.9986243,0.000009922687,0.0004827324,0.0003183025,0.0002450709,0.0003196514],"domain_scores_gemma":[0.9990461,0.000073311,0.0001454747,0.0001572394,0.0005073496,0.0000704557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005130855,0.000380981,0.00009184753,0.001054327,0.0002865489,0.000005375252,0.002915377,0.02990851,0.09773175,0.313229,0.02253975,0.5313435],"study_design_scores_gemma":[0.0000873895,0.0002100031,0.00004241187,0.0003788969,0.00005485085,0.00001034941,0.0009041597,0.436152,0.541851,0.01683331,0.003120975,0.0003546267],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7828608,0.00009177559,0.1930075,0.002657435,0.00136172,0.001880004,0.000108999,0.004457322,0.01357439],"genre_scores_gemma":[0.9951273,0.00003900913,0.004457126,0.0000910333,0.00007833104,0.00006727267,0.0000191283,0.00003329902,0.00008746179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5309888,"threshold_uncertainty_score":0.8328957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05689012104607689,"score_gpt":0.2545655123770461,"score_spread":0.1976753913309692,"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."}}