{"id":"W4221111679","doi":"10.5772/intechopen.102841","title":"Behavioral Biometrics: Past, Present and Future","year":2022,"lang":"en","type":"book-chapter","venue":"IntechOpen eBooks","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Biometrics; Authentication (law); Computer science; Behavioral pattern; Resource (disambiguation); Behavioral modeling; Behavioral analysis; Identity (music); Computer security; Human–computer interaction; Artificial intelligence; Psychology; Applied psychology; Computer network","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":[0.000257688,0.0003045623,0.0003437736,0.0006803164,0.000169598,0.000398914,0.001492371,0.0002263614,0.0004651901],"category_scores_gemma":[0.000001609015,0.0002951174,0.0001342304,0.00007278549,0.00008493195,0.0001456068,0.001381957,0.0005370192,0.0001244285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009649326,"about_ca_system_score_gemma":0.00007128611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006009531,"about_ca_topic_score_gemma":0.000006717873,"domain_scores_codex":[0.9981143,0.00003854019,0.0003954927,0.0006502568,0.000575766,0.0002256108],"domain_scores_gemma":[0.9984467,0.00004112879,0.0002350521,0.001017076,0.0001017492,0.0001583032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007585399,0.00004571348,0.000009635773,0.00005577954,0.00008618338,0.0001064035,0.01199839,1.944779e-8,0.000041056,0.518479,0.01968551,0.4494846],"study_design_scores_gemma":[0.0001616675,0.0001099339,0.0000067787,0.00002891961,0.00002198448,0.00006313788,0.00005011785,0.0001334298,0.00003985272,0.007446201,0.9916133,0.0003246448],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00007558307,0.001162642,0.002033473,0.002424676,0.002172541,0.001102135,0.00006960456,0.0003732811,0.990586],"genre_scores_gemma":[0.01581241,0.0000989336,0.00101418,0.0004729183,0.001740878,0.000143772,0.00003876634,0.0000842231,0.9805939],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9719278,"threshold_uncertainty_score":0.9999501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03484614073371583,"score_gpt":0.2713177734280622,"score_spread":0.2364716326943464,"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."}}