{"id":"W7127180331","doi":"10.1109/trustcom66490.2025.00245","title":"Comparing Reconstruction Attacks on Pretrained Versus Full Fine-tuned Large Language Model Embeddings on Homo Sapiens Splice Sites Genomic Data","year":2025,"lang":"","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Pipeline (software); Language model; Focus (optics); Vulnerability (computing); Embedding; Process (computing); Natural language","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":[0.002987649,0.001363172,0.0006222163,0.0005722667,0.0005279855,0.0009405911,0.0009309057,0.001203996,0.001332993],"category_scores_gemma":[0.01721116,0.0003500076,0.0008616229,0.0005022943,0.001245331,0.003628334,0.00197726,0.002228222,0.001029611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008374553,"about_ca_system_score_gemma":0.001114208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003197233,"about_ca_topic_score_gemma":0.00327996,"domain_scores_codex":[0.9972256,0.001039387,0.0002310042,0.0006416176,0.0005526798,0.0003096807],"domain_scores_gemma":[0.9937032,0.00319147,0.0003734902,0.002134279,0.0004497047,0.0001479237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00268705,0.000478349,0.01770766,0.0006486679,0.0004913888,0.0006860291,0.0004200889,0.6636879,0.02598487,0.009968466,0.01530644,0.2619331],"study_design_scores_gemma":[0.00007942496,0.0005722537,0.002530209,0.00006195434,0.00007184239,0.0003036383,0.0002092777,0.957648,0.02533155,0.009848474,0.003291758,0.00005163502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8799922,0.002620942,0.1001488,0.001866309,0.0004638518,0.0001347511,0.002163192,0.008159891,0.004450007],"genre_scores_gemma":[0.964608,0.0005100622,0.02820491,0.0004157482,0.00005361186,0.00007401217,0.004083032,0.0003106294,0.001740041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003197233,"threshold_uncertainty_score":0.01580042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.077565133690379,"score_gpt":0.3317937504606531,"score_spread":0.2542286167702741,"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."}}