{"id":"W2131656707","doi":"10.24908/ss.v1i1.3390","title":"Surveillance Studies: understanding visibility, mobility and the phenetic fix.","year":2002,"lang":"en","type":"article","venue":"Surveillance & Society","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Visibility; Politics; Dimension (graph theory); Discipline; Economic Justice; Inequality; Sociology; Public relations; Transit (satellite); Data science; Political science; Computer science; Social science; Geography; Law; Public transport","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":[0.01037276,0.0004566337,0.000589434,0.007801245,0.002895156,0.006851671,0.001153695,0.002335988,0.003081888],"category_scores_gemma":[0.04970529,0.0003798369,0.0002916113,0.007660294,0.01615999,0.01735274,0.006307827,0.001588097,0.0001733946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002146542,"about_ca_system_score_gemma":0.002843206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006527211,"about_ca_topic_score_gemma":0.006651202,"domain_scores_codex":[0.9921673,0.006113089,0.000283299,0.0006479155,0.0005489176,0.0002395001],"domain_scores_gemma":[0.9549409,0.03519825,0.005107393,0.002001893,0.001564988,0.001186386],"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":[0.00003285525,0.00004122763,0.04632291,0.0005435303,0.00005640429,0.0003814742,0.0611448,0.0004751759,0.0001868122,0.7990373,0.007067,0.08471046],"study_design_scores_gemma":[0.00001486166,0.00005578101,0.03261906,0.001709924,0.00004112967,0.0007640202,0.05312742,0.00175255,0.0001349842,0.8386462,0.07110504,0.00002903584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.2592741,0.1530478,0.1650267,0.2524563,0.001663435,0.0002551564,0.001298665,0.0001681397,0.1668098],"genre_scores_gemma":[0.962979,0.01796163,0.01352473,0.002373708,0.0005835327,0.0001672609,0.0002149257,0.00002753797,0.002167805],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9971048,"threshold_uncertainty_score":0.05485702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08610161037472018,"score_gpt":0.3274772068123996,"score_spread":0.2413755964376794,"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."}}