{"id":"W2891482866","doi":"10.1049/iet-bmt.2018.5067","title":"Biometric ontology for semantic biometric‐as‐a‐service (BaaS) applications: a border security use case","year":2018,"lang":"en","type":"article","venue":"IET Biometrics","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Semtech (Canada)","funders":"","keywords":"Biometrics; Computer science; Ontology; Identification (biology); Focus (optics); Modalities; Cloud computing; Analytics; Data science; Computer security","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","bibliometrics","scholarly_communication","insufficient_payload"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.001894432,0.0005190381,0.0006305696,0.03030607,0.0008363664,0.001203685,0.002438358,0.000584065,0.000128837],"category_scores_gemma":[0.003322085,0.0005235758,0.0002890559,0.1891936,0.0003388804,0.001294858,0.0006982975,0.000289961,0.001149829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003081658,"about_ca_system_score_gemma":0.0003035053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001650789,"about_ca_topic_score_gemma":0.0002315352,"domain_scores_codex":[0.9949726,0.0001882095,0.001094047,0.0016629,0.0009639905,0.001118196],"domain_scores_gemma":[0.9913807,0.002060503,0.0006209354,0.002315172,0.003045783,0.0005769043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000139094,0.005224829,0.005264045,0.001039603,0.000666726,0.0005156781,0.002709176,0.000001652075,0.002694472,0.1222213,0.04979271,0.8097307],"study_design_scores_gemma":[0.002056062,0.0007458706,0.002189825,0.00001636148,0.000122877,0.001881471,0.0001733568,0.02538064,0.003915236,0.00638689,0.9559042,0.00122722],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04321007,0.002156412,0.9465463,0.002289891,0.002029266,0.002169729,0.0003495234,0.0007307961,0.000518007],"genre_scores_gemma":[0.9051111,0.0003700556,0.08932638,0.003164768,0.0005095917,0.0005402067,0.0001647997,0.00006651974,0.0007465499],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9061115,"threshold_uncertainty_score":0.9998332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04949952315023018,"score_gpt":0.3452606515007424,"score_spread":0.2957611283505122,"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."}}