{"id":"W4413145210","doi":"10.2139/ssrn.5377845","title":"The Case for Inadmissibility of Surreptitious Interceptions","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Computational biology; Pharmacology; Biology","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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.005131531,0.0002325916,0.0003251938,0.000152306,0.0007409117,0.0002166467,0.002099058,0.000187492,0.000004222894],"category_scores_gemma":[0.001120788,0.0001784191,0.0003847323,0.000204175,0.0001134344,0.0001563993,0.001336778,0.004739771,0.000001251029],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00182344,"about_ca_system_score_gemma":0.007511563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003272906,"about_ca_topic_score_gemma":0.003003749,"domain_scores_codex":[0.9969153,0.000368447,0.0006315768,0.000430762,0.0002121218,0.001441743],"domain_scores_gemma":[0.9972215,0.0007265927,0.000630867,0.0009314672,0.0004185741,0.00007097998],"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":[0.00004335786,0.00006182647,0.0001629374,0.00008908793,0.0002935847,0.00002699488,0.0004625534,0.0108989,0.000007408429,0.8445127,0.0002029804,0.1432377],"study_design_scores_gemma":[0.0003824178,0.0001582067,0.00003739816,0.0001017621,0.00006770646,0.001589057,0.001024749,0.06771341,0.00001334219,0.9277219,0.000986932,0.0002031474],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008926427,0.001260799,0.9852454,0.001928502,0.001577473,0.000395194,0.00001345321,0.00005847542,0.0005942787],"genre_scores_gemma":[0.9845347,0.0009506759,0.01219501,0.00003931675,0.0003140931,0.00004341797,0.000004694527,0.00001418289,0.001903922],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9756083,"threshold_uncertainty_score":0.9981149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01508130895788428,"score_gpt":0.313265948427207,"score_spread":0.2981846394693227,"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."}}