{"id":"W2871253773","doi":"10.1109/tvcg.2018.2854737","title":"The Influence of Label Design on Search Performance and Noticeability in Wide Field of View Augmented Reality Displays","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Computer science; Augmented reality; Field of view; Metric (unit); Computer vision; Virtual reality; Visual search; Field (mathematics); Display size; Set (abstract data type); Artificial intelligence; Human–computer interaction; Display device; Mathematics","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":[0.0006523929,0.0001098282,0.0001476113,0.0001480379,0.0002576807,0.00003972049,0.0002785212,0.00006635451,0.00000101941],"category_scores_gemma":[0.000009728607,0.00008940159,0.00002363592,0.0008245263,0.0003144526,0.0001921672,0.00001016997,0.0001426514,7.356871e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001721417,"about_ca_system_score_gemma":0.00004243519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008257113,"about_ca_topic_score_gemma":0.00009106439,"domain_scores_codex":[0.9987355,0.0002376945,0.0003674373,0.0002753702,0.0002456736,0.000138276],"domain_scores_gemma":[0.9985108,0.0007017119,0.0001064013,0.0004204161,0.0002077895,0.00005284638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004836371,0.002509009,0.006385746,0.0006669159,0.0001523828,0.00000109416,0.00693077,0.04747293,0.0006035676,0.822678,0.0001781852,0.1119378],"study_design_scores_gemma":[0.0003778737,0.0006794111,0.02787963,0.0001203505,0.000009320596,0.0000016296,0.00001608541,0.9610969,0.009076945,0.0005954094,0.0000537782,0.00009264126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2818405,0.000008316762,0.717601,0.0002210427,0.00003670487,0.0002574154,0.000003319328,0.00002107478,0.0000106341],"genre_scores_gemma":[0.998302,0.0004749126,0.0008009659,0.0003847806,0.000005541615,0.00002161557,8.809498e-7,0.000004673882,0.000004597353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.913624,"threshold_uncertainty_score":0.3645691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03393657214962277,"score_gpt":0.3180839805679305,"score_spread":0.2841474084183078,"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."}}