{"id":"W4220932283","doi":"10.1155/2022/6044540","title":"Analysis of Key Commuting Routes Based on Spatiotemporal Trip Chain","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Key (lock); Dynamic time warping; DBSCAN; Computer science; Cluster analysis; Data mining; Mode (computer interface); Artificial intelligence; Fuzzy clustering","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":[0.0002786769,0.0004047532,0.0002796905,0.002586928,0.0003134481,0.0007252759,0.0004921127,0.000227859,0.001148294],"category_scores_gemma":[0.001413252,0.0001332588,0.0004872885,0.002210287,0.0002055066,0.001035945,0.0005248602,0.0002379173,0.0003248741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004175975,"about_ca_system_score_gemma":0.0007782262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0134509,"about_ca_topic_score_gemma":0.01055379,"domain_scores_codex":[0.9996734,0.00003455523,0.00003656497,0.0001233198,0.00008932838,0.00004284106],"domain_scores_gemma":[0.9995271,0.00009499644,0.0001093252,0.00004993521,0.0001888607,0.00002973013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002893201,0.0001330058,0.2893961,0.0004989263,0.0002596232,0.0009617623,0.0009306363,0.2359481,0.01276256,0.02156912,0.003802286,0.4334485],"study_design_scores_gemma":[0.00001260904,0.0001239155,0.08776259,0.00004879298,0.0001356891,0.0005812123,0.00132049,0.884198,0.008506289,0.009781476,0.007476912,0.0000520695],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5403377,0.000466768,0.4501407,0.0002189957,0.00004093681,0.00023399,0.003534798,0.0003861786,0.004639935],"genre_scores_gemma":[0.9356433,0.0003522557,0.05934643,0.00001267821,0.0000140487,0.00008078371,0.003107389,0.00002177194,0.001421422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0134509,"threshold_uncertainty_score":0.0267452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0152494258827472,"score_gpt":0.2943666906058297,"score_spread":0.2791172647230825,"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."}}