{"id":"W4321505814","doi":"10.1214/22-sts877","title":"A Conversation with Mary E. Thompson","year":2023,"lang":"en","type":"article","venue":"Statistical Science","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Waterloo; Royal Society; Royal Society of Canada","keywords":"Honour; Medal; Annals; Gold medal; Library science; Conversation; Statistician; Management; Sociology; Mathematics; History; Political science; Law; Classics; Statistics; Art history; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.009274711,0.0008228167,0.00134282,0.001175882,0.009050353,0.007267341,0.001881992,0.009677402,0.01082246],"category_scores_gemma":[0.05766397,0.0005928563,0.0006881862,0.00167691,0.005261641,0.009642718,0.004213113,0.0216858,0.004534997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004779611,"about_ca_system_score_gemma":0.007430043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01255488,"about_ca_topic_score_gemma":0.01684549,"domain_scores_codex":[0.9924657,0.003137867,0.0002839877,0.001041496,0.002177035,0.0008939664],"domain_scores_gemma":[0.9782045,0.0113778,0.0008713719,0.0004700757,0.003582806,0.005493497],"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":[0.0000153959,0.00001516813,0.0002545034,0.00003361558,0.000005805347,0.0001797976,0.002624251,0.00001750118,0.00005199194,0.006839302,0.9820557,0.007906982],"study_design_scores_gemma":[0.000007576958,0.00001985174,0.0004330178,0.0002655502,0.00000435382,0.0004865689,0.005207453,0.00006185923,0.00006120815,0.004810908,0.9886126,0.00002916224],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.0007487975,0.009206078,0.000294453,0.9573296,0.02520187,0.000007350799,0.00003977236,0.00002746407,0.007144585],"genre_scores_gemma":[0.01902288,0.009697119,0.0008055409,0.9088723,0.01875478,0.00006205493,0.00005651685,0.0001906122,0.0425382],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01255488,"threshold_uncertainty_score":0.04904991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01362446477603719,"score_gpt":0.2841100491595704,"score_spread":0.2704855843835332,"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."}}