{"id":"W4412510611","doi":"10.1007/978-981-96-7008-6_31","title":"Role-Playing Based on Large Language Models via Style Extraction","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Style (visual arts); Extraction (chemistry); Computer science; Natural language processing; Artificial intelligence; Information retrieval; Art; Chromatography; Literature; Chemistry","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":[0.001321576,0.001674349,0.001209748,0.002102226,0.000797439,0.002497528,0.00179684,0.001118676,0.01046808],"category_scores_gemma":[0.004484006,0.0009009208,0.00222444,0.001967693,0.0004616833,0.004006937,0.001411786,0.002475674,0.01081448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007077428,"about_ca_system_score_gemma":0.001136112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003065569,"about_ca_topic_score_gemma":0.005895167,"domain_scores_codex":[0.9987639,0.0003968954,0.00009403138,0.0003502906,0.0002847219,0.0001102347],"domain_scores_gemma":[0.9973832,0.00163482,0.0001022134,0.0004213544,0.0003537386,0.0001046961],"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":[0.0006949421,0.0003371442,0.002284685,0.0005460776,0.0001993564,0.0004574328,0.0005174887,0.03086849,0.04388925,0.02144926,0.02997912,0.8687768],"study_design_scores_gemma":[0.0000713031,0.00009262087,0.0008415347,0.00005238367,0.0001279026,0.0003392588,0.0001743688,0.924705,0.01823262,0.03897281,0.01633036,0.00005978798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01010341,0.0006812814,0.9712007,0.0002664791,0.00018343,0.0001770508,0.00211307,0.01098621,0.004288394],"genre_scores_gemma":[0.2626332,0.001036629,0.7115695,0.0002729813,0.0002507849,0.0003232111,0.009955459,0.002449066,0.01150913],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01046808,"threshold_uncertainty_score":0.03501928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03160991546587157,"score_gpt":0.2982491380845073,"score_spread":0.2666392226186358,"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."}}