{"id":"W7096318177","doi":"","title":"1 Security Analysis of Vancouver Pay-By-Phone Parking System","year":2014,"lang":"en","type":"article","venue":"","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Login; Authentication (law); Phone; Security analysis; Security system; Password","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003831265,0.0004305273,0.0003604702,0.001490847,0.001717664,0.001334219,0.0004811693,0.0006206639,0.005506323],"category_scores_gemma":[0.002242345,0.0002101638,0.0003842031,0.0007032995,0.001129106,0.001369291,0.0007027528,0.0005151451,0.0007707488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002634166,"about_ca_system_score_gemma":0.001901405,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04518981,"about_ca_topic_score_gemma":0.03079644,"domain_scores_codex":[0.998546,0.0001635563,0.00004207466,0.0001260478,0.000581591,0.0005408104],"domain_scores_gemma":[0.998098,0.0006408834,0.0001798686,0.0002873215,0.0006973406,0.00009654043],"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":[0.002848377,0.0004591238,0.09942581,0.000839117,0.000286035,0.007721188,0.002622547,0.4045328,0.1446524,0.1917443,0.02503927,0.1198291],"study_design_scores_gemma":[0.00002906456,0.0002683043,0.02224121,0.00004057419,0.00007158783,0.001415102,0.000643287,0.9308844,0.02495585,0.01246983,0.006906156,0.00007460943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9537362,0.0003380896,0.01436088,0.0004006678,0.00002684283,0.0001792961,0.0004787043,0.0006188494,0.02986044],"genre_scores_gemma":[0.9968312,0.00004861531,0.0008851932,0.00002008122,0.000002484386,0.000008073133,0.0001220154,0.00001106102,0.002071268],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9548102,"threshold_uncertainty_score":0.08985353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005905488634379409,"score_gpt":0.216042268124937,"score_spread":0.2101367794905576,"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."}}