{"id":"W7044384303","doi":"","title":"Whose national security? Canadian state surveillance and the creation of enemies","year":2000,"lang":"en","type":"article","venue":"","topic":"Global Security and Public Health","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"State (computer science); Government (linguistics); Legislation; Agency (philosophy)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002700965,0.0002471327,0.0003162143,0.002004886,0.01523514,0.008677368,0.001305995,0.001859232,0.008739913],"category_scores_gemma":[0.0126746,0.0002553324,0.0002912356,0.003482364,0.009532124,0.002666432,0.002959277,0.00381286,0.0002210835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1170045,"about_ca_system_score_gemma":0.175415,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958631,"about_ca_topic_score_gemma":0.9982699,"domain_scores_codex":[0.9973283,0.0003274925,0.00003863697,0.0001561141,0.0006661576,0.001483379],"domain_scores_gemma":[0.9926823,0.001216486,0.0008460673,0.0002366153,0.002908317,0.002110116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002196179,0.0001006187,0.1373935,0.0001743059,0.00007621379,0.0006132268,0.09065651,0.001058253,0.0004030135,0.580407,0.09674769,0.09215001],"study_design_scores_gemma":[0.00004671707,0.00004911845,0.2280553,0.0006196478,0.0001238738,0.0002707609,0.2453733,0.001101926,0.0005205296,0.03570609,0.4879612,0.0001714178],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4093643,0.008369945,0.0007936095,0.1989469,0.000610621,0.00006629673,0.0007433182,0.00002618774,0.3810789],"genre_scores_gemma":[0.9808463,0.003049496,0.0002509108,0.002584809,0.00006458,0.000008198149,0.00009483378,0.00001082697,0.01308997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1170045,"threshold_uncertainty_score":0.8489311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009357723634940907,"score_gpt":0.2841632138611275,"score_spread":0.2748054902261866,"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."}}