{"id":"W3188586497","doi":"10.1109/tits.2021.3095765","title":"A Dynamic Ridesplitting Method With Potential Pick-Up Probability Based on GPS Trajectories","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Global Positioning System; Computer science; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008901614,0.001125799,0.001790293,0.002169145,0.000799068,0.001243634,0.002900084,0.001192081,0.004194212],"category_scores_gemma":[0.003162712,0.0008581876,0.001501934,0.002519283,0.000516387,0.002155022,0.001327242,0.00141515,0.00132312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008995073,"about_ca_system_score_gemma":0.002412464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02333435,"about_ca_topic_score_gemma":0.01429657,"domain_scores_codex":[0.999151,0.0001124589,0.00006423267,0.0003378005,0.0002157952,0.0001187496],"domain_scores_gemma":[0.9990891,0.0003347255,0.00008179671,0.000117915,0.0002935864,0.00008281995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003455071,0.0001421354,0.004394963,0.0001968562,0.000110717,0.000133921,0.0001524403,0.5382088,0.00370453,0.004824616,0.007853536,0.439932],"study_design_scores_gemma":[0.00002213486,0.00002147999,0.0002538986,0.000006727672,0.00001415584,0.00002833699,0.00001904085,0.9968688,0.0004680886,0.00119231,0.001093715,0.00001134382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02040311,0.0004778085,0.9739615,0.0002057761,0.00008206764,0.0001457036,0.0004585352,0.002798077,0.001467474],"genre_scores_gemma":[0.424796,0.0007097984,0.5633833,0.0002250055,0.0001927228,0.0004485619,0.003239636,0.0005082014,0.006496658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02333435,"threshold_uncertainty_score":0.04639709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01630353332429276,"score_gpt":0.2504028060098083,"score_spread":0.2340992726855155,"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."}}