{"id":"W2248830513","doi":"10.1109/kaleidoscope.2015.7383624","title":"Privacy, consumer trust and big data: Privacy by design and the 3 C'S","year":2015,"lang":"en","type":"article","venue":"","topic":"Access Control and Trust","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Safeguard; Big data; Internet privacy; Consumer privacy; Information privacy; Computer security; Business; Computer science; Scale (ratio); Privacy by Design; Democracy; Political science; Law","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":[0.03630994,0.0006237431,0.0007935854,0.001631749,0.005297853,0.01921565,0.001774004,0.007872098,0.004384382],"category_scores_gemma":[0.0325553,0.0006909285,0.001150185,0.002175007,0.05762717,0.01791557,0.008016365,0.006877675,0.00063071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008991341,"about_ca_system_score_gemma":0.01014168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00441487,"about_ca_topic_score_gemma":0.002604115,"domain_scores_codex":[0.9587052,0.03017318,0.00134199,0.001992582,0.00647684,0.001310254],"domain_scores_gemma":[0.9478861,0.03261067,0.00274805,0.01037712,0.003897082,0.00248095],"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":[0.00002461305,0.00001892423,0.0003425778,0.0000994947,0.0000122813,0.0000542444,0.003605505,0.0001869578,0.0001434482,0.9765605,0.003409022,0.01554243],"study_design_scores_gemma":[0.00002238035,0.00005502125,0.0003728481,0.0002646453,0.00001567217,0.0002204982,0.002325797,0.001318473,0.000389232,0.9171981,0.07778709,0.00003033029],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03306838,0.0162753,0.2505442,0.4265054,0.001615869,0.0003654694,0.0001580402,0.0005354069,0.2709318],"genre_scores_gemma":[0.8737052,0.00655078,0.08232535,0.02053266,0.0009031109,0.0008646942,0.00008120165,0.0002065666,0.01483039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03630994,"threshold_uncertainty_score":0.1920276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1246143593046335,"score_gpt":0.3267068249980526,"score_spread":0.2020924656934191,"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."}}