{"id":"W2898222558","doi":"10.1109/mmul.2018.2873843","title":"Towards a QoE Model to Evaluate Holographic Augmented Reality Devices","year":2018,"lang":"en","type":"article","venue":"IEEE Multimedia","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Augmented reality; Quality of experience; Multimedia; Perspective (graphical); Holography; Human–computer interaction; Inference; Quality of service; Computer network; Artificial intelligence","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":[0.001211798,0.0002263321,0.0002586835,0.0002020927,0.0001772324,0.0001825271,0.001164975,0.0000943095,0.00003701982],"category_scores_gemma":[0.00009926074,0.000199567,0.0001061288,0.0006614421,0.0001347635,0.0005108651,0.0002818452,0.000152393,0.0004885775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007134415,"about_ca_system_score_gemma":0.000202661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004163921,"about_ca_topic_score_gemma":0.0002545639,"domain_scores_codex":[0.9975718,0.0002159447,0.0003736188,0.0006652817,0.0006427501,0.000530608],"domain_scores_gemma":[0.9981659,0.00007703173,0.0001094195,0.00099515,0.000365157,0.0002873616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002198839,0.001489272,0.002570396,0.0001622845,0.0003899153,0.000125762,0.03117293,0.002879491,0.04895392,0.005058497,0.09641013,0.8105675],"study_design_scores_gemma":[0.0006858897,0.000246123,0.009538825,0.00003623034,0.00002259535,0.000004805296,0.00003820566,0.9668556,0.01761587,0.002541048,0.002058004,0.0003567603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09932134,0.00003457585,0.8908164,0.004857366,0.001065492,0.0004369966,0.00001666468,0.0003618749,0.003089282],"genre_scores_gemma":[0.8140341,0.000006154447,0.1817105,0.003708525,0.0002534955,0.0000652221,0.000004925373,0.00001248814,0.0002045388],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9639761,"threshold_uncertainty_score":0.8138108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1085501145762839,"score_gpt":0.3963333568592129,"score_spread":0.287783242282929,"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."}}