{"id":"W7084108788","doi":"10.64628/aam.jkydhwskw","title":"Protecting children’s data privacy in the smart city","year":2019,"lang":"en","type":"article","venue":"","topic":"Brazilian Legal Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Smart city; Information privacy; Confidentiality; Smart card; Field (mathematics); Privacy software","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":[],"consensus_categories":[],"category_scores_codex":[0.01183358,0.0002087302,0.0004937648,0.001163613,0.007078087,0.01053161,0.001175631,0.005244234,0.007179662],"category_scores_gemma":[0.02979405,0.0003693452,0.0006088699,0.002445052,0.01353354,0.006296504,0.006389934,0.006432136,0.0007827795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006280943,"about_ca_system_score_gemma":0.01455442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06535508,"about_ca_topic_score_gemma":0.05653057,"domain_scores_codex":[0.9871611,0.00637837,0.0006322443,0.001270456,0.002782114,0.001775557],"domain_scores_gemma":[0.9751663,0.01555428,0.002157269,0.003019302,0.002787853,0.00131495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000274224,0.00002451003,0.006760566,0.00007900541,0.0000201831,0.0004432557,0.02401971,0.0001983383,0.0003865972,0.9337131,0.01606893,0.01825843],"study_design_scores_gemma":[0.00003163317,0.00005957195,0.01297874,0.001685258,0.0001158897,0.001225106,0.04163926,0.00121832,0.002808698,0.2593277,0.6788276,0.00008222747],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1623219,0.006428964,0.02216044,0.304543,0.0009283607,0.0001544804,0.001139764,0.0001276845,0.5021956],"genre_scores_gemma":[0.9485886,0.00262704,0.005406817,0.02020238,0.000249844,0.0001146221,0.000202319,0.00006082126,0.02254764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06535508,"threshold_uncertainty_score":0.1299493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06744085905036096,"score_gpt":0.3566485921758581,"score_spread":0.2892077331254972,"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."}}