{"id":"W4388757737","doi":"10.1109/uemcon59035.2023.10316060","title":"Intentional Biases in LLM Responses","year":2023,"lang":"en","type":"article","venue":"","topic":"Persona Design and Applications","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Viewpoints; Variety (cybernetics); Persona; Computer science; Construct (python library); Set (abstract data type); Language model; Field (mathematics); Supervisor; Human–computer interaction; Artificial intelligence; Data science; Natural language processing; Programming language","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":[0.0001510644,0.00002813685,0.00003006815,0.0001377627,0.00003070593,0.00003581435,0.0002514069,0.00001165252,0.00003497186],"category_scores_gemma":[0.00006996858,0.00002461667,0.00001710638,0.0007129742,0.00001271209,0.0001117849,0.00007302809,0.0000269292,0.0007560283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001290999,"about_ca_system_score_gemma":0.00003668249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002636874,"about_ca_topic_score_gemma":0.00002314757,"domain_scores_codex":[0.9996136,0.00001912825,0.00006154053,0.0001216773,0.00007949781,0.0001045887],"domain_scores_gemma":[0.999644,0.0001685046,0.000007479821,0.0001409679,0.00001333436,0.00002572953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000006130306,0.0001140161,0.003393267,0.000002369747,0.000003598777,0.00002626327,0.0003600733,0.00006887369,0.0159216,0.9042051,0.05395693,0.02194182],"study_design_scores_gemma":[0.0004823657,0.00006630637,0.4943222,0.00003647765,0.000001294174,0.00002231401,0.0002661358,0.4051313,0.005147038,0.04752648,0.04669323,0.0003048783],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6545373,0.00004085207,0.3008916,0.01912186,0.0001619742,0.0001841132,0.000006930832,0.001136657,0.02391877],"genre_scores_gemma":[0.9809438,0.000008325343,0.007882635,0.0004193907,0.00001273906,0.00003505026,0.000003230496,0.000001757037,0.01069307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8566785,"threshold_uncertainty_score":0.9717466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1068782892838309,"score_gpt":0.3323295776576057,"score_spread":0.2254512883737749,"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."}}