{"id":"W2032819216","doi":"10.1177/1541931213571074","title":"Designing for Interpersonal Trust – The Power of Trust Tokens","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Team Dynamics and Performance","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Interpersonal communication; Information exchange; Computer science; Face (sociological concept); Limiting; Key (lock); Power (physics); Knowledge management; Internet privacy; Psychology; Social psychology; Computer security; Sociology; Engineering; Telecommunications","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":[0.0004411036,0.0001718621,0.0002392065,0.00002034182,0.000427418,0.00005496422,0.0003821069,0.0001158609,0.00005315289],"category_scores_gemma":[0.00003832137,0.0001051697,0.0002729686,0.00006968223,0.00027142,0.0001809375,0.0001522676,0.0002116175,7.77363e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003052492,"about_ca_system_score_gemma":0.00001172941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001917776,"about_ca_topic_score_gemma":0.000002956285,"domain_scores_codex":[0.9990615,0.000006362757,0.0003509229,0.0002108596,0.00008630243,0.0002840823],"domain_scores_gemma":[0.9991438,0.00012492,0.0004088401,0.00009622834,0.0001828829,0.00004327738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001335693,0.0001397653,0.6064314,0.0002953889,0.0004623074,1.731577e-8,0.3241048,0.0000228454,0.03567995,0.01584375,0.01590675,0.000979437],"study_design_scores_gemma":[0.001502917,0.000568937,0.5406529,0.0003092797,0.0001687133,0.000006851641,0.4382023,0.003940989,0.007894914,0.002291943,0.003783103,0.0006771496],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974837,0.00008752127,0.00002269547,0.0001631138,0.0002496153,0.0003568217,0.00005593054,0.00001469664,0.001565905],"genre_scores_gemma":[0.9985397,0.00001291169,0.0007295542,0.0001103301,0.00008857561,0.0000313545,0.000002032063,0.00002418936,0.0004612815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1140975,"threshold_uncertainty_score":0.4288695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01793512049060608,"score_gpt":0.2566893168596923,"score_spread":0.2387541963690862,"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."}}