{"id":"W3035776698","doi":"10.1155/2020/6026140","title":"Privacy Protection Method for Vehicle Trajectory Based on VLPR Data","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Trajectory; Computer science; Generalization; Adversary; License; Tracking (education); Information privacy; Computer security; Privacy protection; Data Protection Act 1998; Data mining; Mathematics","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":[0.002984104,0.0007441651,0.001138989,0.001755498,0.001472781,0.00221491,0.002240733,0.001575289,0.002068275],"category_scores_gemma":[0.01363508,0.0004984154,0.001654605,0.002745555,0.001133195,0.007387578,0.003887509,0.001992272,0.0008204194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001554236,"about_ca_system_score_gemma":0.002289206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002804133,"about_ca_topic_score_gemma":0.001156418,"domain_scores_codex":[0.9938583,0.001400436,0.0004465894,0.001334895,0.002200841,0.0007590311],"domain_scores_gemma":[0.9929569,0.002236123,0.0008157582,0.002764818,0.001036881,0.0001894662],"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":[0.001110182,0.0002308924,0.01122304,0.0004386821,0.0002745743,0.0008662851,0.001430389,0.3264355,0.02478731,0.1604757,0.0112268,0.4615007],"study_design_scores_gemma":[0.00003427444,0.0001189143,0.0008923716,0.00002739589,0.00005414489,0.0006781301,0.0002158463,0.9490374,0.01169516,0.03242163,0.004768656,0.00005610807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02200714,0.0003163733,0.9747268,0.0004190882,0.00006175671,0.0001011896,0.0003242888,0.0005474483,0.001495811],"genre_scores_gemma":[0.8871105,0.0008854794,0.1063328,0.0002602247,0.0001631432,0.0002124117,0.001183013,0.00008868819,0.003763745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002984104,"threshold_uncertainty_score":0.01578164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06972386542386812,"score_gpt":0.3641095276884175,"score_spread":0.2943856622645494,"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."}}