{"id":"W3215899368","doi":"10.3390/digital1040015","title":"Improving Readability of Online Privacy Policies through DOOP: A Domain Ontology for Online Privacy","year":2021,"lang":"en","type":"article","venue":"Digital","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Readability; Jargon; Privacy policy; Computer science; Internet privacy; Ontology; Domain (mathematical analysis); Privacy software; Key (lock); Information privacy; World Wide Web; Action (physics); Reading (process); Computer security; Political science; Law","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003251822,0.0001563456,0.0003305514,0.00004736978,0.0002856214,0.00014546,0.000559436,0.0001691295,0.00003036959],"category_scores_gemma":[0.006449656,0.0001555404,0.0001646751,0.0003283811,0.0003949539,0.001098416,0.0004244012,0.0001569762,0.000003592029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001431591,"about_ca_system_score_gemma":0.0005954465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003604827,"about_ca_topic_score_gemma":0.007402067,"domain_scores_codex":[0.9983053,0.0001134317,0.0004290064,0.0004130718,0.0002959202,0.000443261],"domain_scores_gemma":[0.9984761,0.0003010726,0.0002124298,0.0005987111,0.0003151392,0.00009658386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00122839,0.01332794,0.05808919,0.001570921,0.0005018553,0.00007201274,0.1825518,0.000007773629,0.02402913,0.1891273,0.01002801,0.5194657],"study_design_scores_gemma":[0.001576033,0.0005422942,0.01644667,0.00009171182,0.00006603388,0.00002604215,0.02570178,0.00009983178,0.01035596,0.401431,0.5428981,0.0007646406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810708,0.0002677983,0.007650913,0.005747329,0.0002750349,0.0006053182,0.001942394,0.000121523,0.002318959],"genre_scores_gemma":[0.983068,0.00005741706,0.01491569,0.0002259232,0.000599811,0.00002494499,0.0008077469,0.00001760168,0.0002828195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5328701,"threshold_uncertainty_score":0.7721306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04368870550553924,"score_gpt":0.3446450082676642,"score_spread":0.300956302762125,"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."}}