{"id":"W4205701438","doi":"10.5539/cis.v15n1p47","title":"VR Users Are More Relaxed and Optimistic during COVID Lockdown than Others","year":2022,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Headset; Virtual reality; Feeling; Coronavirus disease 2019 (COVID-19); Immersion (mathematics); Computer science; Human–computer interaction; Optical head-mounted display; Period (music); Positive correlation; Applied psychology; Internet privacy; Psychology; Artificial intelligence; Medicine; Social psychology; Aesthetics; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004830618,0.00009018339,0.00009107457,0.0001879841,0.001188931,0.0006255449,0.0006535333,0.00001541471,0.00000712057],"category_scores_gemma":[0.00004693698,0.0000845865,0.00001604562,0.0008206186,0.0002319533,0.004811433,0.0008280721,0.0001054969,0.000006853685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008020853,"about_ca_system_score_gemma":0.0001136622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002392617,"about_ca_topic_score_gemma":6.816279e-7,"domain_scores_codex":[0.9989307,0.00002066917,0.0002038721,0.0002205603,0.0004054402,0.0002187777],"domain_scores_gemma":[0.9992061,0.0000449014,0.000128562,0.0003375926,0.00007466293,0.0002081675],"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":[0.00008260954,0.0002215078,0.02760606,0.0003302717,0.00004590261,0.00001567739,0.1358372,0.1225305,0.001554389,0.3261535,0.007179763,0.3784426],"study_design_scores_gemma":[0.0005201928,0.0001205637,0.2550523,0.00001676847,0.000002839159,0.0001355452,0.001043857,0.725509,0.0001285458,0.0003579382,0.01685065,0.0002618024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4091054,0.00003497226,0.5873314,0.002150075,0.0001691885,0.0002191545,0.00001550667,0.0001203889,0.0008539465],"genre_scores_gemma":[0.9889581,0.00002835234,0.00912788,0.001830143,0.00001539117,0.00001617462,0.000003308505,0.000002060328,0.00001856013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6029785,"threshold_uncertainty_score":0.9144417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.015852125272109,"score_gpt":0.2526138414901154,"score_spread":0.2367617162180064,"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."}}