{"id":"W4308506790","doi":"10.2196/40119","title":"Impact of Personalized Avatars and Motion Synchrony on Embodiment and Users’ Subjective Experience: Empirical Study","year":2022,"lang":"en","type":"article","venue":"JMIR Serious Games","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute for Information and Communications Technology Promotion; Ministry of Science and ICT, South Korea; National Research Foundation of Korea; National Research Foundation","keywords":"Avatar; Motion (physics); Motion capture; Virtual reality; Perspective (graphical); Agency (philosophy); Psychology; sync; Human–computer interaction; Computer science; Computer vision; Artificial intelligence; Frame (networking)","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":[0.0001917974,0.0001339582,0.0002004208,0.0001086197,0.0002218937,0.00007807607,0.0002427308,0.00002339002,0.0000327309],"category_scores_gemma":[0.0000211525,0.000113962,0.0000417597,0.0003082577,0.00009491272,0.0002153646,0.0003054807,0.0001193293,0.00000148891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001615031,"about_ca_system_score_gemma":0.000068969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002348504,"about_ca_topic_score_gemma":0.000009166135,"domain_scores_codex":[0.9987849,0.0001405699,0.0001719293,0.0003819094,0.0003346389,0.0001860257],"domain_scores_gemma":[0.9993351,0.0000635961,0.00009760071,0.0003523701,0.00003628906,0.0001150534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005580763,0.005394636,0.4147543,0.00004224239,0.0003280265,0.00003859192,0.4037782,0.0006370741,0.006257211,0.003811657,0.002604347,0.1617956],"study_design_scores_gemma":[0.0008486928,0.004093908,0.9858628,0.000005637131,0.00000743359,0.00002725352,0.005553422,0.002705667,0.000161543,0.0002286398,0.0003529712,0.0001520708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981638,0.00009978448,0.0006274023,0.0002125769,0.00003530252,0.0006904816,0.00001715498,0.00004097627,0.0001124998],"genre_scores_gemma":[0.9994133,0.00001738113,0.0001509671,0.00008982747,0.000009502566,0.0002615727,0.000002769269,0.000006837197,0.00004788287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5711085,"threshold_uncertainty_score":0.4647235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0266046685299697,"score_gpt":0.353911698665421,"score_spread":0.3273070301354514,"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."}}