{"id":"W2062402846","doi":"10.1177/1541931214581454","title":"Driver Engagement in Notifications","year":2014,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Smartwatch; Wearable computer; Computer science; Human–computer interaction; Wearable technology; Exploratory research; Internet privacy; Display size; Smartphone application; Multimedia; Embedded system; Operating system; Display device","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":[0.0006002701,0.0001160665,0.0001556691,0.00004002078,0.000358239,0.000040799,0.0001985284,0.00008038973,0.0001243415],"category_scores_gemma":[0.0000713652,0.00009210764,0.0001252085,0.00008662969,0.0001059668,0.0001501755,0.0001032179,0.0002414983,0.000007542237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005499281,"about_ca_system_score_gemma":0.000005647487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009293129,"about_ca_topic_score_gemma":0.00001320661,"domain_scores_codex":[0.9991695,0.00002103903,0.000347622,0.0002135539,0.00007989301,0.0001683531],"domain_scores_gemma":[0.9994159,0.00009896547,0.0002637786,0.00008686904,0.00009503968,0.00003941818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003157376,0.0002537269,0.5411431,0.0001070142,0.0001365579,2.509492e-8,0.2340338,0.00006533337,0.01017759,0.1971737,0.01580406,0.001073499],"study_design_scores_gemma":[0.0004783523,0.00003571414,0.9384971,0.00006911741,0.00002169923,7.569608e-7,0.04115205,0.0005159836,0.00121152,0.0008459871,0.01697951,0.000192226],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836937,0.00001043319,0.00001330231,0.0002155042,0.000261045,0.0001309565,0.000008534378,0.0000329328,0.01563361],"genre_scores_gemma":[0.9986496,0.000006457464,0.0002216199,0.0001419538,0.00007452419,0.00001363701,0.000002537585,0.00001253718,0.0008771284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.397354,"threshold_uncertainty_score":0.3756041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.028348228403157,"score_gpt":0.2998274575722117,"score_spread":0.2714792291690547,"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."}}