{"id":"W2998768595","doi":"10.5539/nct.v5n1p11","title":"Bernardo Autonomous Emotional Agents Increase Perception of VR Stimuli","year":2020,"lang":"en","type":"article","venue":"Network and Communication Technologies","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Narrative; Interactivity; Perception; Gesture; Video game; Empathy; Psychology; Virtual reality; Cognitive psychology; Virtuality (gaming); Nonverbal communication; Multimedia; Computer science; Human–computer interaction; Social psychology; Communication; Art; Artificial intelligence","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":[0.0001485211,0.00008515434,0.0001289519,0.0000378914,0.0001767249,0.00005429902,0.0009806616,0.00009110526,0.000008914149],"category_scores_gemma":[0.00009911197,0.00008101872,0.00002567655,0.0003778423,0.0001618046,0.000233364,0.0007471882,0.0001494031,0.00001219014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002035742,"about_ca_system_score_gemma":0.00002838361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004117923,"about_ca_topic_score_gemma":0.00000309406,"domain_scores_codex":[0.999314,0.00005387932,0.0002100623,0.0001762174,0.000120704,0.0001250976],"domain_scores_gemma":[0.9989493,0.00007592714,0.0001337248,0.0007273972,0.00006694299,0.00004663793],"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":[0.000007228158,0.00005690805,0.0009764718,0.00001388435,0.00001578289,2.433326e-7,0.0005191361,0.0008396078,0.0003341748,0.1470143,0.00350928,0.846713],"study_design_scores_gemma":[0.0009976841,0.0008115835,0.1178758,0.0001782615,0.0000407484,0.00002169957,0.002740575,0.6153775,0.0007813886,0.1491329,0.1113574,0.0006844165],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2002717,0.003106948,0.731595,0.05384485,0.00004931751,0.0006074558,0.00001890504,0.002224031,0.008281771],"genre_scores_gemma":[0.9452118,0.001883961,0.05249183,0.0003471643,0.00001194202,0.00001970528,0.00001547372,0.00000387629,0.00001420435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8460286,"threshold_uncertainty_score":0.3303847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04110839689159664,"score_gpt":0.2774024958634632,"score_spread":0.2362940989718666,"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."}}