{"id":"W4235380641","doi":"10.32920/ryerson.14652744.v1","title":"Emotional Immersion Through Interactive Media","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Brock University","funders":"","keywords":"Sadness; Disgust; Anger; Interactivity; Happiness; CLIPS; Psychology; Immersion (mathematics); Multimedia; Variety (cybernetics); Video game; Computer science; Social psychology; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001577489,0.0002353258,0.0002597978,0.00007556344,0.00007526723,0.0004264904,0.001506714,0.0002284485,0.001163706],"category_scores_gemma":[0.0001547876,0.0002181725,0.0001992715,0.0001864498,0.00007958335,0.0006818391,0.004086309,0.0006690561,0.0004657306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001380065,"about_ca_system_score_gemma":0.0002845767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003796472,"about_ca_topic_score_gemma":0.00006497119,"domain_scores_codex":[0.9979928,0.0001094118,0.0003510479,0.000817853,0.0004808049,0.0002481126],"domain_scores_gemma":[0.9982103,0.0003597185,0.0001646515,0.0008783721,0.0003169575,0.00006996527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003116271,0.0008915862,0.0008487057,0.0001655843,0.0004647171,0.0004702186,0.08620188,0.008617888,0.002300333,0.4117697,0.03717216,0.451066],"study_design_scores_gemma":[0.0001435857,0.00009215067,0.00273124,0.00122733,0.00004322155,0.00009153505,0.0114751,0.2782476,0.3333313,0.3642916,0.006256186,0.002069217],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01112473,0.0001950625,0.9602288,0.002644471,0.005273738,0.0001332847,0.000003739276,0.0001859869,0.02021016],"genre_scores_gemma":[0.7896682,0.0001270804,0.2083211,0.0008857173,0.0003439219,0.00002005728,0.0000475605,0.00001421984,0.0005720846],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7785435,"threshold_uncertainty_score":0.9997494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06003857748232906,"score_gpt":0.328067555300594,"score_spread":0.268028977818265,"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."}}