{"id":"W2604877886","doi":"","title":"“Windows to our Inner Private Lives”: Cell Phones, Informational Privacy and the Power to Search Incident to Arrest in Canada","year":2015,"lang":"en","type":"article","venue":"Lex Electronica","topic":"Criminal Law and Evidence","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Humanities; Political science; Law; History; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001445884,0.0001796944,0.000401745,0.001578258,0.02433065,0.01028733,0.002267397,0.002898347,0.01183777],"category_scores_gemma":[0.01034758,0.0003814053,0.0003303249,0.002895737,0.01043192,0.002745026,0.005840922,0.005949131,0.0004549398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08545619,"about_ca_system_score_gemma":0.145378,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9951482,"about_ca_topic_score_gemma":0.9981492,"domain_scores_codex":[0.9956785,0.0004348438,0.00009641393,0.0002439892,0.0009946529,0.002551622],"domain_scores_gemma":[0.9928504,0.001730932,0.0006007007,0.0001707012,0.001913811,0.002733471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002089086,0.0001923756,0.1340054,0.0003246012,0.00006766861,0.002574117,0.4631463,0.001013489,0.000734726,0.227412,0.101692,0.06862836],"study_design_scores_gemma":[0.00002884251,0.00004168328,0.1218535,0.0004747944,0.0000527281,0.0003627074,0.6740877,0.0007951783,0.0002985803,0.008219902,0.193633,0.0001513691],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6769036,0.003532787,0.001013018,0.1236212,0.0005215554,0.0001375728,0.0007192387,0.00003514855,0.1935159],"genre_scores_gemma":[0.9708815,0.001464456,0.00009001321,0.004436394,0.00004426177,0.00001904732,0.00007534655,0.00002142451,0.02296765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08545619,"threshold_uncertainty_score":0.6200309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02217838711404264,"score_gpt":0.2920404382587863,"score_spread":0.2698620511447437,"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."}}