{"id":"W4319165505","doi":"10.1016/j.bushor.2023.02.001","title":"Can behavioral biometrics make everyone happy?","year":2023,"lang":"en","type":"article","venue":"Business Horizons","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria; Queen's University","funders":"","keywords":"Biometrics; Internet privacy; Transparency (behavior); Business; Behavioral pattern; Identity (music); Focus (optics); Iris recognition; Work (physics); Marketing; Computer science; Computer security; Engineering","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":[0.003138038,0.000339915,0.0004084272,0.0007132483,0.002329834,0.005064547,0.0005982387,0.002216849,0.01586031],"category_scores_gemma":[0.0158914,0.0002341818,0.0003139877,0.0005248432,0.00230825,0.01126447,0.002291671,0.003466974,0.007113756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008288046,"about_ca_system_score_gemma":0.001102749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008813294,"about_ca_topic_score_gemma":0.001725702,"domain_scores_codex":[0.9986445,0.0005681794,0.00002933246,0.0001219837,0.0003199471,0.0003159883],"domain_scores_gemma":[0.9932417,0.001990148,0.0009547169,0.0005137168,0.001187475,0.002112377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007075755,0.0005061574,0.02934771,0.000193021,0.0001010302,0.0005501347,0.003619722,0.000331827,0.002530084,0.1944858,0.2347487,0.5328782],"study_design_scores_gemma":[0.00005714901,0.0004464724,0.03245496,0.0005431926,0.0001070215,0.0009933927,0.02153159,0.001830584,0.002676414,0.5098621,0.4293395,0.0001575508],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1147689,0.01091978,0.01431868,0.5965409,0.01233068,0.00003129717,0.0003977443,0.0003877127,0.2503044],"genre_scores_gemma":[0.8933344,0.007018987,0.004913213,0.04137868,0.003196791,0.00004689568,0.0001891524,0.0001313091,0.04979055],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01586031,"threshold_uncertainty_score":0.05305803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0454777134119544,"score_gpt":0.2833770687518083,"score_spread":0.2378993553398539,"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."}}