{"id":"W2143630872","doi":"10.24908/ss.v1i3.3344","title":"Sousveillance: Inventing and Using Wearable Computing Devices for Data Collection in Surveillance Environments.","year":2002,"lang":"en","type":"article","venue":"Surveillance & Society","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":819,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Wearable computer; Computer science; Variety (cybernetics); Wearable technology; Data collection; Computer security; Data science; Human–computer interaction; Real-time computing; Artificial intelligence; Embedded system","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.00140945,0.0007956124,0.0003581463,0.0011199,0.0005227248,0.002242045,0.001054065,0.0014808,0.001976885],"category_scores_gemma":[0.003078983,0.0004112049,0.0004558222,0.0007246134,0.001191589,0.003969958,0.002152186,0.0009780378,0.0009636226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002283873,"about_ca_system_score_gemma":0.0003039229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005957686,"about_ca_topic_score_gemma":0.0009779936,"domain_scores_codex":[0.998881,0.0003564441,0.00006530243,0.0002402767,0.000385412,0.00007157753],"domain_scores_gemma":[0.9990483,0.0004112415,0.0001050819,0.0001714265,0.0001908928,0.00007309792],"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":[0.0002694147,0.0001418515,0.005139375,0.001498343,0.00008748108,0.0005351455,0.003742037,0.0008915567,0.07117309,0.04274806,0.01205541,0.8617182],"study_design_scores_gemma":[0.00005493566,0.001076141,0.01817615,0.001552069,0.0002419321,0.007083683,0.002414207,0.01716642,0.1389418,0.02684205,0.7860861,0.0003645044],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04881103,0.0379838,0.8551192,0.002485142,0.001496832,0.0005590261,0.0002905441,0.002927364,0.05032712],"genre_scores_gemma":[0.2940744,0.0338137,0.6373105,0.002594133,0.001185371,0.0006153291,0.0008249072,0.0003362266,0.02924543],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9994773,"threshold_uncertainty_score":0.007453978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06799808037248435,"score_gpt":0.2985852485658634,"score_spread":0.2305871681933791,"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."}}