{"id":"W4416193476","doi":"10.1145/3773071","title":"Designing Augmented Reality for Cyclists: How Text-Based Notification Placements Influence Attentional Tunneling and Cycling Experience","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Augmented reality; Popularity; Field (mathematics); Cycling; User experience design; Event (particle physics); Human factors and ergonomics","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":[0.0005116773,0.000200443,0.0001925169,0.0002358346,0.0006098177,0.0004017274,0.001668187,0.00007723524,0.000001289853],"category_scores_gemma":[0.0003934146,0.0001795684,0.0001033712,0.0004198407,0.0001054632,0.0009556295,0.0006103579,0.0002105704,0.000001242546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002288378,"about_ca_system_score_gemma":0.00003227126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000270239,"about_ca_topic_score_gemma":0.000002696432,"domain_scores_codex":[0.9982923,0.00002498174,0.0004698973,0.0006529359,0.0003337081,0.0002261803],"domain_scores_gemma":[0.9979477,0.0003284021,0.0006046277,0.000585386,0.0004873522,0.00004654434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001990101,0.000640289,0.006238839,0.0006108974,0.0001634884,1.866075e-7,0.002242388,0.01129078,0.8755621,0.07711764,0.00365479,0.02227956],"study_design_scores_gemma":[0.001331919,0.0001461848,0.04106848,0.001397954,0.00005892817,0.000005263536,0.0004643969,0.565443,0.3731196,0.0158347,0.0007457173,0.0003838655],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3556238,0.000005627384,0.6380406,0.005223585,0.0002504507,0.0006500099,0.000004363646,0.0001040217,0.00009753176],"genre_scores_gemma":[0.9333735,0.000002368882,0.06569565,0.000466763,0.00005963185,0.0002990956,0.000009936713,0.000009893967,0.00008322745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5777496,"threshold_uncertainty_score":0.7322586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06602762397070401,"score_gpt":0.3593268513558618,"score_spread":0.2932992273851578,"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."}}