{"id":"W3047743253","doi":"10.48550/arxiv.2008.03872","title":"Barometers Can Hear, and Sense Finger Taps","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Barometer; Touchscreen; Permission; Computer science; Sample (material); Speech recognition; Real-time computing; Computer security; Artificial intelligence; Human–computer interaction; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004500156,0.0009309486,0.0005040462,0.0008285567,0.0002747652,0.0008401141,0.0007305964,0.001010296,0.003195225],"category_scores_gemma":[0.004291758,0.0004671501,0.0002794219,0.0003797247,0.000513311,0.001328969,0.00129131,0.0007980543,0.002158119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001940871,"about_ca_system_score_gemma":0.0001826097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005620415,"about_ca_topic_score_gemma":0.0006321146,"domain_scores_codex":[0.9991354,0.00009861341,0.00004117213,0.0001670587,0.0004387383,0.0001189601],"domain_scores_gemma":[0.9981411,0.0007170311,0.0003755491,0.0003070614,0.0003566794,0.0001026454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009104596,0.0001820986,0.02695425,0.0007700594,0.0001114682,0.001269083,0.0009300243,0.002425118,0.5920329,0.003669182,0.01014549,0.3605999],"study_design_scores_gemma":[0.0001799761,0.002168266,0.09375554,0.0004812654,0.0002974705,0.00916012,0.0009172782,0.1099627,0.6819251,0.01045215,0.09031646,0.0003836035],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5869694,0.009331273,0.3582448,0.001265292,0.001551702,0.0003618814,0.001557869,0.01394984,0.02676793],"genre_scores_gemma":[0.9493397,0.001276538,0.03997858,0.0006733068,0.0003415483,0.0001026745,0.0003176536,0.0001553946,0.007814555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003195225,"threshold_uncertainty_score":0.01068908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06926459182144387,"score_gpt":0.1816173323350181,"score_spread":0.1123527405135742,"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."}}