{"id":"W2890555171","doi":"10.1145/3236495","title":"Persona","year":2018,"lang":"en","type":"article","venue":"Computers in entertainment","topic":"Persona Design and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul","keywords":"Persona; Computer science; Avatar; Support vector machine; Artificial intelligence; Facial expression; Set (abstract data type); Expression (computer science); Feature selection; Action (physics); Feature (linguistics); Face (sociological concept); Human–computer interaction; Pattern recognition (psychology); Computer vision","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":[],"consensus_categories":[],"category_scores_codex":[0.000122321,0.00009382659,0.00008614044,0.00009362683,0.0000706943,0.00007014765,0.0007724056,0.00002499999,0.00001389738],"category_scores_gemma":[0.000003189422,0.0000910176,0.00003717701,0.0002450307,0.00006150968,0.000132694,0.0002115775,0.00006223172,0.0001796681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009898387,"about_ca_system_score_gemma":0.0000191042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000110137,"about_ca_topic_score_gemma":0.00000555873,"domain_scores_codex":[0.9991305,0.00003172812,0.0001342272,0.0003145022,0.0001555861,0.0002334848],"domain_scores_gemma":[0.9994468,0.0000328255,0.00002913188,0.0004017133,0.00002016341,0.00006938436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002037968,0.0009325066,0.00916992,0.00002396432,0.00004865645,0.00008027745,0.01873452,0.00005710612,0.006230467,0.5298495,0.04814645,0.3867063],"study_design_scores_gemma":[0.002166516,0.0005813014,0.03054298,0.0001567068,0.000005891962,0.00006667632,0.000338081,0.7954951,0.004080203,0.01948135,0.1461962,0.0008889446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02584116,0.000040299,0.965703,0.001901048,0.0004161368,0.0001446043,5.48837e-7,0.0001107365,0.005842441],"genre_scores_gemma":[0.9082472,0.000005751195,0.08975465,0.001740414,0.0001032401,0.00002799881,0.000001099995,0.000004435939,0.0001151855],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8824061,"threshold_uncertainty_score":0.371159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01279793565446876,"score_gpt":0.2494737101369993,"score_spread":0.2366757744825305,"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."}}