{"id":"W4360994723","doi":"10.22329/tclr.v1i2.7931","title":"Admissibility of Hearsay Gathered Under MLAT: A Tempest in Canada","year":2023,"lang":"en","type":"article","venue":"Transnational Criminal Law Review","topic":"Criminal Law and Evidence","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Hearsay; Law; State (computer science); Tempest; Political science; Admissible evidence; Work (physics); Resistance (ecology); Engineering; Computer science; Computer security","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.01657231,0.0002529826,0.0008373106,0.003445064,0.01796146,0.009066931,0.003437805,0.003280249,0.002852122],"category_scores_gemma":[0.04732031,0.0005607202,0.0004666165,0.007172999,0.007888304,0.002079835,0.003673551,0.004922085,0.0002460392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.108,"about_ca_system_score_gemma":0.2681304,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9965219,"about_ca_topic_score_gemma":0.9990141,"domain_scores_codex":[0.9872233,0.001765529,0.000724529,0.001031565,0.006271316,0.002983893],"domain_scores_gemma":[0.9434932,0.01837307,0.001461987,0.001318443,0.0321096,0.003243576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007997307,0.0002483031,0.1142216,0.002332492,0.0004352907,0.01004004,0.1508664,0.002689988,0.002342032,0.2568214,0.1283826,0.3308201],"study_design_scores_gemma":[0.0001510789,0.0002934584,0.241522,0.004253645,0.0009161549,0.002077188,0.2047857,0.00323045,0.004028545,0.01754253,0.5206454,0.0005536622],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6272751,0.04357534,0.002213824,0.1197797,0.001006826,0.0003828687,0.001984485,0.00007763368,0.2037043],"genre_scores_gemma":[0.9571475,0.0112923,0.001663112,0.01072006,0.0000987796,0.00003519969,0.0003609121,0.00003942686,0.01864274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.108,"threshold_uncertainty_score":0.7835982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08576572488900898,"score_gpt":0.3644951672580238,"score_spread":0.2787294423690149,"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."}}