{"id":"W4408592422","doi":"10.1109/ieeedata.2025.3553097","title":"Descriptor: Multimodal Dataset for Player Engagement Analysis in Video Games (MultiPENG)","year":2025,"lang":"en","type":"article","venue":"IEEE data descriptions.","topic":"Digital Games and Media","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Video game; Human–computer interaction; Multimedia; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009832638,0.002989561,0.001432264,0.002843751,0.0009003857,0.001389817,0.002407887,0.00227756,0.0115662],"category_scores_gemma":[0.003037055,0.0003680033,0.00167415,0.002393431,0.000380236,0.001093063,0.002407826,0.001502482,0.01728074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001145429,"about_ca_system_score_gemma":0.001003923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02675043,"about_ca_topic_score_gemma":0.03755806,"domain_scores_codex":[0.998903,0.0001767941,0.0001310403,0.0002966363,0.000317122,0.0001754082],"domain_scores_gemma":[0.998924,0.0001755116,0.0000827855,0.0003200555,0.0003529312,0.0001446825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001102649,0.0006541344,0.009031503,0.001589549,0.0002833517,0.0004300733,0.0002008578,0.0040018,0.007424447,0.0009950406,0.8905792,0.08370745],"study_design_scores_gemma":[0.001093538,0.001196789,0.1305761,0.0005891378,0.0003269441,0.001182018,0.0009062893,0.05103284,0.01887299,0.00373553,0.790046,0.0004418399],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01714221,0.0006075343,0.003903573,0.0002605609,0.0002950034,0.000621578,0.967298,0.006597486,0.003273954],"genre_scores_gemma":[0.01126522,0.0001045977,0.003213225,0.00007457749,0.00003637148,0.0006716761,0.9827477,0.0001324591,0.001754092],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02675043,"threshold_uncertainty_score":0.05318946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1007772799875307,"score_gpt":0.3837966642882122,"score_spread":0.2830193843006815,"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."}}