{"id":"W2355603571","doi":"","title":"Canadian Electronic Evidence Act Breaking through Traditional Evidence Rules in Common Law System","year":2006,"lang":"en","type":"article","venue":"Hebei faxue","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hearsay; Federal Rules of Evidence; Legislation; Authentication (law); Law; Electronic records; Reliability (semiconductor); Rules of evidence; Business; Political science; Computer science; Database","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002661514,0.0001877537,0.0002204444,0.00008793238,0.0001733651,0.0004082394,0.0008678707,0.00007763072,0.000005977241],"category_scores_gemma":[0.00001251743,0.0001830444,0.00007633195,0.0004287707,0.00008034123,0.002638757,0.00008255987,0.00022467,0.0001412974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009219957,"about_ca_system_score_gemma":0.0005503235,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3015432,"about_ca_topic_score_gemma":0.5083285,"domain_scores_codex":[0.9981189,0.00007065474,0.0003217694,0.000426155,0.0003794118,0.0006830827],"domain_scores_gemma":[0.9990843,0.0002380686,0.00007806624,0.000433195,0.00005225116,0.0001141372],"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":[0.000003204518,0.00002189575,0.001922938,0.00003345407,0.000004271529,0.00009604863,0.0001090913,0.0001659189,0.00004045366,0.9946329,0.0007905778,0.002179241],"study_design_scores_gemma":[0.0008911545,0.0005007705,0.1091881,0.008108482,0.00003949067,0.001402173,0.0001743261,0.02766281,0.003615469,0.8019128,0.04424484,0.002259532],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8131634,0.007710217,0.01742403,0.007488658,0.00121893,0.0008267314,0.00007050281,0.0007090722,0.1513884],"genre_scores_gemma":[0.9980016,0.00001690802,0.001081946,0.0005816627,0.0001204587,0.00002351752,0.00001101465,0.00001145035,0.0001514063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2067853,"threshold_uncertainty_score":0.7464334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03209881255212452,"score_gpt":0.2320343890251664,"score_spread":0.1999355764730419,"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."}}