{"id":"W3209819052","doi":"10.32920/ryerson.14652657.v1","title":"Avatarme: digital avatars in a theme park queue creating a better experience and an emotional connection","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Media Influence and Health","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Theme park; Theme (computing); Avatar; Queue; Computer science; Crowds; Documentation; Human–computer interaction; Advertising; World Wide Web; Computer security; Business; Tourism; History; Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007640306,0.0004262851,0.0001768625,0.0002697745,0.000894478,0.002425392,0.0004886572,0.0008208096,0.01944292],"category_scores_gemma":[0.002459363,0.000172344,0.000376011,0.0001548962,0.0008122114,0.002548814,0.002959509,0.0008924851,0.002487547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000185003,"about_ca_system_score_gemma":0.000217031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003400558,"about_ca_topic_score_gemma":0.0008543818,"domain_scores_codex":[0.9996081,0.0002255491,0.00001057263,0.00004718523,0.00005604255,0.00005258865],"domain_scores_gemma":[0.9992484,0.0002997323,0.00005341581,0.00007849909,0.0000755048,0.0002443569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002922673,0.00271991,0.03595124,0.00208812,0.000129819,0.004390941,0.2750159,0.001875398,0.1905216,0.06170142,0.09176426,0.3309188],"study_design_scores_gemma":[0.0006073709,0.004983556,0.03301262,0.0007108522,0.0002273548,0.01001763,0.1377631,0.01413173,0.02989972,0.01829753,0.7499935,0.0003550005],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8157158,0.0005929084,0.07790021,0.002485718,0.0009447125,0.0003197409,0.0004126433,0.001928586,0.09969973],"genre_scores_gemma":[0.9108571,0.0002640669,0.03886572,0.0005426963,0.0001556637,0.0002524665,0.0002664041,0.0004048842,0.04839093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01944292,"threshold_uncertainty_score":0.06504303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0655990227920927,"score_gpt":0.3033283759369629,"score_spread":0.2377293531448702,"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."}}