{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01940295,0.001190596,0.002528012,0.001612086,0.002825773,0.005403396,0.005355833,0.01599856,0.01573727],"category_scores_gemma":[0.2100613,0.001529408,0.001837055,0.001356573,0.007379865,0.01359512,0.007006615,0.01563689,0.00466163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001454057,"about_ca_system_score_gemma":0.001818337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006714803,"about_ca_topic_score_gemma":0.0004527688,"domain_scores_codex":[0.9816568,0.005466828,0.001255988,0.004457495,0.004479153,0.002683704],"domain_scores_gemma":[0.7898037,0.1106388,0.01297195,0.07715443,0.007088466,0.002342592],"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":[0.001221705,0.0001631025,0.009513289,0.0003770774,0.0003633764,0.004477555,0.001602232,0.04201955,0.005582622,0.8352129,0.02082777,0.07863887],"study_design_scores_gemma":[0.0001144043,0.0001780337,0.001335787,0.0001862867,0.0001236086,0.003467866,0.0003032371,0.09867844,0.006556622,0.8750981,0.01385876,0.00009877951],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1503308,0.001856119,0.7042836,0.02974705,0.00147641,0.0002887522,0.001056227,0.003720452,0.1072406],"genre_scores_gemma":[0.9564611,0.0003382778,0.02777386,0.001972993,0.000448781,0.000122818,0.0001942547,0.0004093053,0.01227862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01940295,"threshold_uncertainty_score":0.1026139,"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."}}