{"id":"W4416371006","doi":"10.48550/arxiv.2510.03035","title":"Protecting Persona Biometric Data: The Case of Facial Privacy","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Harm; Identity theft; Biometrics; Information privacy; Face (sociological concept); Privacy by Design; Identity (music); Intellectual property; Data Protection Act 1998","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01811568,0.0003829189,0.0005591681,0.001631776,0.005822537,0.008075655,0.001541533,0.01090734,0.002647434],"category_scores_gemma":[0.02435596,0.0004317346,0.00108239,0.002040302,0.01933634,0.01237396,0.00625762,0.008006258,0.000656804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005371506,"about_ca_system_score_gemma":0.004845184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01063679,"about_ca_topic_score_gemma":0.007241888,"domain_scores_codex":[0.979565,0.01060939,0.0006815323,0.001765263,0.005906115,0.001472612],"domain_scores_gemma":[0.9802896,0.01429543,0.001100753,0.00276161,0.001357086,0.0001955803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001220683,0.000009480651,0.0007022139,0.00006792684,0.000009330428,0.0005658841,0.002524049,0.0003173362,0.0002179941,0.9762176,0.003897155,0.01545877],"study_design_scores_gemma":[0.00002120272,0.00004339262,0.002656472,0.001175376,0.00004914271,0.002880248,0.005705237,0.00286839,0.004091578,0.6114068,0.3690138,0.00008838023],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07571909,0.04587937,0.07578517,0.2565055,0.001287003,0.0001740267,0.0003758045,0.0001064198,0.5441677],"genre_scores_gemma":[0.9008753,0.02369448,0.01806284,0.03343555,0.001131068,0.0002513306,0.0001186224,0.00005907999,0.02237168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01811568,"threshold_uncertainty_score":0.09580606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1603075017661752,"score_gpt":0.3816752543075521,"score_spread":0.2213677525413769,"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."}}