{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003580828,0.0003561832,0.0004264651,0.0007590396,0.001690418,0.002888857,0.001197812,0.0011064,0.001441425],"category_scores_gemma":[0.006524431,0.0003786958,0.0008278911,0.000807751,0.001694346,0.006342737,0.004172007,0.001762917,0.0003177923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009693519,"about_ca_system_score_gemma":0.001884473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002573814,"about_ca_topic_score_gemma":0.002860368,"domain_scores_codex":[0.9980083,0.0007773826,0.0001762474,0.0003058626,0.0005473185,0.0001850036],"domain_scores_gemma":[0.9954059,0.001183802,0.0003611124,0.001835268,0.0009406187,0.0002733285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000829787,0.0005729673,0.0104945,0.0005366313,0.0001539772,0.002142169,0.005914979,0.07162734,0.0481575,0.546432,0.005960654,0.3071775],"study_design_scores_gemma":[0.0001145616,0.0003734696,0.002480372,0.0002679157,0.0002503,0.001674215,0.001391288,0.5173796,0.04467486,0.3629926,0.06826482,0.0001358841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02694021,0.000360041,0.96463,0.0009000467,0.00009331715,0.0002251051,0.00007388163,0.0009266697,0.005850712],"genre_scores_gemma":[0.6831644,0.0008635594,0.3101264,0.0003191895,0.00009413499,0.0001838372,0.0001925731,0.0001652979,0.004890608],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003580828,"threshold_uncertainty_score":0.01893741,"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."}}