{"id":"W4403048309","doi":"10.1007/978-981-96-0576-7_15","title":"Synthetic Data: Generate Avatar Data on Demand","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Agence Nationale de la Recherche; Natural Sciences and Engineering Research Council of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec","keywords":"Avatar; Computer science; Human–computer interaction","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003586078,0.0003077536,0.0003670194,0.0004835781,0.0007085455,0.0008167049,0.005306958,0.0002548248,0.0003737284],"category_scores_gemma":[0.0004454541,0.000271396,0.00006188244,0.0005368889,0.001735482,0.000476447,0.001492816,0.0006734404,0.0003884685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002498866,"about_ca_system_score_gemma":0.001083358,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001121654,"about_ca_topic_score_gemma":0.01966888,"domain_scores_codex":[0.9958625,0.00008583341,0.0003752632,0.002113829,0.001103745,0.0004588354],"domain_scores_gemma":[0.995315,0.0007064082,0.0001233721,0.003561313,0.0001350214,0.0001589512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001242305,0.00009237146,0.00004072738,0.0001417803,0.00009873394,0.000141165,0.004928856,0.04746893,0.00002658145,0.05791686,0.001547132,0.8875844],"study_design_scores_gemma":[0.00009727823,0.00006479282,0.00001422939,0.0006804276,0.0001294674,0.000003047458,0.000004117524,0.7169566,0.00006214114,0.14155,0.1397111,0.0007268177],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001155202,0.001917855,0.9646976,0.00434741,0.002133416,0.0004589249,0.0003342331,0.0001638799,0.02583119],"genre_scores_gemma":[0.9439427,0.00117486,0.02398773,0.005388527,0.007964677,0.00001622486,0.001389964,0.0001244038,0.0160109],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9438272,"threshold_uncertainty_score":0.9999738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05958938339946626,"score_gpt":0.322429213828239,"score_spread":0.2628398304287727,"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."}}