{"id":"W3072329718","doi":"10.3390/info11080399","title":"Preventative Nudges: Introducing Risk Cues for Supporting Online Self-Disclosure Decisions","year":2020,"lang":"en","type":"article","venue":"Information","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Universität Duisburg-Essen; Deutsche Forschungsgemeinschaft; European Commission","keywords":"Nudge theory; Internet privacy; SAFER; Risk perception; Perception; Private information retrieval; Computer science; Work (physics); Computer security; Psychology; Social psychology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.000835453,0.00007664069,0.0001039661,0.00005725064,0.0006827847,0.0001467272,0.0002325493,0.00007276749,0.00004399188],"category_scores_gemma":[0.009361728,0.0000740271,0.00005602251,0.0002556427,0.00003286174,0.002802164,0.00008896847,0.0001395521,0.00005777828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007690192,"about_ca_system_score_gemma":0.0001326966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006093744,"about_ca_topic_score_gemma":0.0004884348,"domain_scores_codex":[0.998964,0.0001019328,0.0003701106,0.000113041,0.0002529608,0.0001979667],"domain_scores_gemma":[0.999019,0.0002090511,0.0003403296,0.0001222808,0.0002087305,0.0001005955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001419568,0.0001159934,0.004667174,0.0001200787,0.00007789804,4.161957e-7,0.6090503,0.000308959,0.00007355722,0.006991968,0.04007578,0.3383759],"study_design_scores_gemma":[0.001900442,0.0004806987,0.008491853,0.00008693218,0.0001463927,0.00000165361,0.1623219,0.03546144,0.001379573,0.03331305,0.7558169,0.0005990741],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5913846,0.00009382008,0.3737451,0.02424941,0.0009933118,0.003069823,0.001303352,0.0009615699,0.004199013],"genre_scores_gemma":[0.9676544,0.0002641029,0.0294232,0.0008844194,0.0009879832,0.00006479322,0.0006991951,0.00000761819,0.0000142741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7157412,"threshold_uncertainty_score":0.9989828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0357087967049944,"score_gpt":0.3462563621759767,"score_spread":0.3105475654709823,"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."}}