{"id":"W4408359794","doi":"10.2196/72527","title":"Authors’ Response to Peer Reviews of “Data Obfuscation Through Latent Space Projection for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection”","year":2025,"lang":"en","type":"article","venue":"JMIRx Med","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Obfuscation; Corporate governance; Projection (relational algebra); Space (punctuation); Internet privacy; Business; Computer science; Computer security; Data science; Finance; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01837998,0.0009070215,0.001878172,0.001556262,0.006177678,0.007991793,0.002800669,0.03960143,0.02088505],"category_scores_gemma":[0.2798847,0.0008997365,0.001760927,0.00146717,0.003618821,0.00350232,0.003972783,0.02708805,0.01495001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00460693,"about_ca_system_score_gemma":0.01263622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0108761,"about_ca_topic_score_gemma":0.01524024,"domain_scores_codex":[0.97393,0.005989617,0.004239846,0.002321568,0.0116939,0.00182515],"domain_scores_gemma":[0.7761356,0.08275092,0.01092961,0.004735914,0.1200901,0.00535793],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002285382,0.000007392441,0.0001242794,0.0001046156,0.00001296416,0.000121387,0.0001770211,0.00003866372,0.00006930076,0.0006160643,0.9956583,0.003047258],"study_design_scores_gemma":[0.00004220127,0.00002107069,0.0007894385,0.0006553932,0.00003904901,0.0002936851,0.0009025965,0.000542603,0.0004104106,0.002033402,0.9941881,0.00008215394],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.0002685437,0.001147599,0.0005554057,0.8819568,0.1136812,0.00004039806,0.0002521671,0.0001083371,0.001989663],"genre_scores_gemma":[0.007881995,0.002178696,0.001400172,0.8563516,0.1157644,0.0002386209,0.0001681933,0.0002027395,0.01581357],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.98162,"threshold_uncertainty_score":0.09720379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2141077808011656,"score_gpt":0.5258479293827707,"score_spread":0.311740148581605,"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."}}