{"id":"W4205717276","doi":"10.1126/science.ada0055","title":"Artificial intelligence unmasks anonymous chess players","year":2022,"lang":"en","type":"article","venue":"Science","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"Computer science; Software; Computer security; Internet privacy","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":[0.002937706,0.0004685085,0.0003828859,0.0007591568,0.001087542,0.002707277,0.0008300985,0.001167929,0.004874224],"category_scores_gemma":[0.01851872,0.0003150946,0.0003220982,0.0006209089,0.00150913,0.002479739,0.002510002,0.001337506,0.001934546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006887144,"about_ca_system_score_gemma":0.001157231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002681563,"about_ca_topic_score_gemma":0.002578534,"domain_scores_codex":[0.9968905,0.0008247665,0.0001182848,0.0006141939,0.001185035,0.0003672538],"domain_scores_gemma":[0.9876336,0.004270057,0.001803783,0.004106369,0.001304288,0.0008819306],"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":[0.004043595,0.001023176,0.2155053,0.0001479642,0.0003775987,0.0008399921,0.00399851,0.04245901,0.0452597,0.1680411,0.02372005,0.4945838],"study_design_scores_gemma":[0.0001907753,0.001304012,0.08070015,0.0001335331,0.0002031546,0.001268363,0.003589358,0.4663773,0.0568748,0.3204007,0.06880433,0.0001533968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8366503,0.0001062261,0.08582496,0.00415877,0.0002573964,0.0001052084,0.0003567259,0.001950727,0.07058971],"genre_scores_gemma":[0.9849284,0.00002778486,0.008161746,0.0003754521,0.00004876948,0.00001731747,0.0001423171,0.00009439049,0.006203905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004874224,"threshold_uncertainty_score":0.01630592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07127328360725943,"score_gpt":0.2487286259430801,"score_spread":0.1774553423358207,"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."}}