{"id":"W4225924369","doi":"10.1155/2022/8030690","title":"Knowledge Graph-Based Enhanced Transformer for Metro Individual Travel Destination Prediction","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Travel time; Travel behavior; Entropy (arrow of time); Graph; Data mining; Transport engineering; Machine learning; Engineering; Theoretical computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003037198,0.0006243197,0.0006685344,0.001506329,0.0003546659,0.0006084046,0.001158576,0.0005855195,0.001570587],"category_scores_gemma":[0.001546997,0.0002628701,0.0008140516,0.00143426,0.0003021827,0.001901515,0.0009583648,0.0007229822,0.0004986269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005787801,"about_ca_system_score_gemma":0.0008878206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01665776,"about_ca_topic_score_gemma":0.02042061,"domain_scores_codex":[0.9997154,0.00003675629,0.0000148612,0.0001030604,0.00008643427,0.00004352144],"domain_scores_gemma":[0.9995344,0.0001660479,0.00006079207,0.00008820219,0.0001171249,0.00003354712],"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":[0.0003450257,0.0002848973,0.01618156,0.0002187454,0.0001804026,0.0003517762,0.0002562512,0.3561024,0.01014413,0.00943901,0.005934644,0.6005611],"study_design_scores_gemma":[0.000007179617,0.0000404303,0.001712649,0.000005917789,0.00003374034,0.00007876785,0.00005463207,0.9914145,0.001852963,0.003894086,0.0008944676,0.00001072092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07227665,0.0003073694,0.9223679,0.0001688813,0.00003617218,0.00007829198,0.0007071372,0.001836867,0.002220676],"genre_scores_gemma":[0.8850748,0.0003210721,0.1098183,0.00008680137,0.00003075523,0.00006591406,0.001783912,0.00007157129,0.002746982],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01665776,"threshold_uncertainty_score":0.03312165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02223453689833021,"score_gpt":0.3108978929600785,"score_spread":0.2886633560617483,"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."}}