{"id":"W4399126753","doi":"10.1109/vrw62533.2024.00408","title":"Target Selection with Avatars in Mixed Reality","year":2024,"lang":"en","type":"article","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Avatar; Selection (genetic algorithm); Computer science; Virtual reality; Mixed reality; Fitts's law; Human–computer interaction; Artificial intelligence; Engineering","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":[0.0002214974,0.00005932358,0.00005753239,0.00008675063,0.00003700079,0.0001004619,0.0002394336,0.00002917104,0.00002694251],"category_scores_gemma":[0.000004718782,0.00004579447,0.00001379689,0.0009515976,0.00001947323,0.0003068543,0.00005483037,0.0001080358,0.00008338154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008193609,"about_ca_system_score_gemma":0.00008032935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005136435,"about_ca_topic_score_gemma":0.0009298188,"domain_scores_codex":[0.9993054,0.00003050217,0.0001121945,0.0002880251,0.000132199,0.0001316491],"domain_scores_gemma":[0.9996476,0.00003294912,0.00001282796,0.0002488232,0.00002208992,0.00003576797],"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":[0.000005448158,0.0001281883,0.001592249,0.00004438301,0.00002887319,0.00001573186,0.0005466188,0.004203412,0.001466918,0.9442394,0.0233013,0.02442745],"study_design_scores_gemma":[0.0001571383,0.00005663747,0.01448522,0.00003351695,0.000004025845,0.00003490808,0.00003466114,0.8961712,0.008337445,0.02386282,0.05662878,0.0001936512],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003669813,0.0000248889,0.9800504,0.005242549,0.00005856257,0.0001388956,0.000001919782,0.0004225772,0.01039036],"genre_scores_gemma":[0.9380971,0.00000583759,0.06051308,0.0001651018,0.00002646104,0.00006342764,0.000009902573,0.000006182071,0.001112924],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9344273,"threshold_uncertainty_score":0.1867445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01527020868360902,"score_gpt":0.2612139998385374,"score_spread":0.2459437911549284,"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."}}