{"id":"W4293863531","doi":"10.1109/siu55565.2022.9864837","title":"User Identification on Smartphones with Motion Sensors and Touching Behaviors","year":2022,"lang":"en","type":"article","venue":"2022 30th Signal Processing and Communications Applications Conference (SIU)","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Identification (biology); Computer science; Motion (physics); Motion sensors; Human–computer interaction; Computer vision","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005418704,0.0001965959,0.0001867004,0.0002615409,0.002510307,0.0006392593,0.001239814,0.00004780211,0.00002839636],"category_scores_gemma":[0.000007859039,0.0001967105,0.00002916043,0.0008101346,0.0002182893,0.0004980708,0.0005705181,0.0004123013,0.00001284853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006622434,"about_ca_system_score_gemma":0.0001346489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006028807,"about_ca_topic_score_gemma":0.00003018817,"domain_scores_codex":[0.9981183,0.0002819582,0.0004067497,0.0005728814,0.0004079779,0.0002121759],"domain_scores_gemma":[0.9978084,0.0001298061,0.0003180905,0.001390195,0.0002346304,0.0001188713],"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":[0.00003765346,0.001215392,0.004926431,0.0001595908,0.00006068555,0.000002068342,0.04500718,0.0002220603,0.008469046,0.3731649,0.0002537438,0.5664813],"study_design_scores_gemma":[0.001491846,0.0004416303,0.02444249,0.0001781281,0.0001839533,0.0002381872,0.01563172,0.8780666,0.001434231,0.01488577,0.06146707,0.001538397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2580331,0.001490259,0.7261543,0.01030948,0.00006406888,0.001766797,0.00006383563,0.000623446,0.001494739],"genre_scores_gemma":[0.9940135,0.0001207835,0.003450106,0.0001883885,0.00001549826,0.001576395,0.0000942132,0.00001777984,0.0005233738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8778445,"threshold_uncertainty_score":0.9987883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02476851219313635,"score_gpt":0.2642775936753032,"score_spread":0.2395090814821669,"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."}}