{"id":"W2800301733","doi":"10.3390/mti2020018","title":"Enhancing Privacy in Wearable IoT through a Provenance Architecture","year":2018,"lang":"en","type":"article","venue":"Multimodal Technologies and Interaction","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Pennsylvania State University","keywords":"Wearable computer; Provenance; Internet of Things; Architecture; Computer science; Internet privacy; Wearable technology; Computer security; Human–computer interaction; Embedded system; Art; Geology; Visual arts","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001219471,0.0001314394,0.0001397029,0.0001377397,0.000151938,0.0001206401,0.0004019653,0.0001222094,0.000001193267],"category_scores_gemma":[0.0001801857,0.0001110872,0.00002704734,0.000349133,0.00009676209,0.0004427592,0.0004754761,0.0003545374,0.00001749797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006443486,"about_ca_system_score_gemma":0.00001635085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002931846,"about_ca_topic_score_gemma":0.00003065611,"domain_scores_codex":[0.999014,0.00001935565,0.0001966978,0.0003813353,0.0000877954,0.0003008619],"domain_scores_gemma":[0.9994822,0.00005584734,0.00008767716,0.0003167771,0.00004394809,0.00001360943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002271926,0.00005450688,0.001148045,0.00002836435,0.000006694518,0.000007095085,0.002885225,0.00003189061,0.02925759,0.0009052283,0.0002416998,0.9654109],"study_design_scores_gemma":[0.001012857,0.0008715569,0.009022238,0.0009673756,0.000004773774,0.000133739,0.001335202,0.3070594,0.5574839,0.04055703,0.08082377,0.0007281964],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7768264,0.0002203332,0.2163952,0.001964648,0.002423728,0.0001919383,7.899191e-8,0.0007557198,0.001221923],"genre_scores_gemma":[0.9146916,0.00004338228,0.08489801,0.00006909182,0.0002313841,0.00001416583,2.498319e-7,0.000006179354,0.0000459671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9646828,"threshold_uncertainty_score":0.4530004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01676560445353851,"score_gpt":0.2757380931689631,"score_spread":0.2589724887154246,"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."}}