{"id":"W3080122153","doi":"10.1007/978-3-030-57404-8_25","title":"“Most Companies Share Whatever They Can to Make Money!”: Comparing User’s Perceptions with the Data Practices of IoT Devices","year":2020,"lang":"en","type":"book-chapter","venue":"IFIP advances in information and communication technology","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Notice; Internet privacy; Transparency (behavior); Data sharing; Internet of Things; Computer science; Computer security; Privacy policy; Information privacy; Perception; Software deployment; Psychology","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":[0.001644745,0.0001710219,0.00009395432,0.0005011391,0.001172313,0.003135667,0.0004572957,0.00100793,0.004705234],"category_scores_gemma":[0.007004257,0.0001487131,0.0002546714,0.000937583,0.001634499,0.004754615,0.001378065,0.001320978,0.001096685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008538744,"about_ca_system_score_gemma":0.0007817518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009527938,"about_ca_topic_score_gemma":0.01085611,"domain_scores_codex":[0.9988819,0.0005868587,0.00004821789,0.00005123813,0.0003191992,0.0001125021],"domain_scores_gemma":[0.9960521,0.002438498,0.0006004264,0.0001302749,0.0004657386,0.0003130472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001965571,0.0003049102,0.1716342,0.0001995432,0.00004776229,0.000548334,0.6501281,0.000204941,0.00130822,0.01873289,0.05029323,0.1064013],"study_design_scores_gemma":[0.000007776939,0.0001468536,0.2023566,0.0002321147,0.00002039091,0.0004620556,0.7507055,0.0003796541,0.0004668318,0.00206793,0.04310814,0.00004615119],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9230344,0.0009425577,0.001059178,0.009029021,0.0001304441,0.00003356003,0.0003130867,0.00003007091,0.06542775],"genre_scores_gemma":[0.9889928,0.0006682034,0.0004342312,0.001545299,0.00002131398,0.00004232813,0.0001677863,0.00001489833,0.008113255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009527938,"threshold_uncertainty_score":0.01894498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05761164718726784,"score_gpt":0.3391094192500572,"score_spread":0.2814977720627894,"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."}}