{"id":"W2943694314","doi":"10.1007/978-3-030-18419-3_4","title":"Mobile Travel Credentials","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Computer graphics (images)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001084668,0.0004221334,0.0005203446,0.001747737,0.0001935888,0.0009459199,0.004454466,0.0003856357,0.0001284369],"category_scores_gemma":[0.00006531439,0.0004000971,0.0001769722,0.001373172,0.0004815384,0.0005894859,0.00115683,0.0006354317,0.0005402275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002485202,"about_ca_system_score_gemma":0.0007577694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002339959,"about_ca_topic_score_gemma":0.00001951715,"domain_scores_codex":[0.9959648,0.00003551941,0.0005690977,0.001622701,0.001240401,0.0005675156],"domain_scores_gemma":[0.9970663,0.0002588113,0.0003089093,0.001905604,0.0002870367,0.0001733665],"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":[0.000002814107,0.00006142914,0.00002589224,0.00005888125,0.00001481686,0.00004046141,0.001073601,0.001603598,0.0005082562,0.07076555,0.0002741201,0.9255706],"study_design_scores_gemma":[0.001048961,0.0006069224,0.0009284941,0.0004846373,0.00002870797,0.0002060735,8.577873e-7,0.6314642,0.01135101,0.2654789,0.08559828,0.002802956],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003552971,0.0008726066,0.9846963,0.0002042207,0.003828012,0.0005306472,0.00001008932,0.0001268642,0.009695722],"genre_scores_gemma":[0.3819474,0.0004446538,0.5878182,0.004156387,0.00115285,0.00004009297,0.00003895346,0.0001017494,0.02429973],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9227676,"threshold_uncertainty_score":0.9998451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221153016003468,"score_gpt":0.2602474960792216,"score_spread":0.2380359659191869,"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."}}