{"id":"W4399838215","doi":"10.48550/arxiv.2406.12843","title":"Can Go AIs be adversarially robust?","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut de Valorisation des Données","keywords":"Econometrics; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002804709,0.0008224557,0.0007472973,0.000681091,0.0009113959,0.00150802,0.001643836,0.002641977,0.004382586],"category_scores_gemma":[0.01982919,0.0004702581,0.0007720061,0.0003138599,0.005065982,0.004151346,0.00329277,0.002758756,0.001297635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007164057,"about_ca_system_score_gemma":0.0008267565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001149611,"about_ca_topic_score_gemma":0.0010224,"domain_scores_codex":[0.9984192,0.0004609647,0.00006042472,0.0003811715,0.0004094497,0.0002688463],"domain_scores_gemma":[0.9907251,0.004851901,0.001051511,0.002587926,0.0004597278,0.0003238298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002041724,0.0000905006,0.004737129,0.0003140486,0.000204749,0.0002633067,0.0004514199,0.6848932,0.02270016,0.2154602,0.005311747,0.06536948],"study_design_scores_gemma":[0.00002816324,0.0002356868,0.001427809,0.00009382278,0.00004207639,0.0003424826,0.0001924436,0.6592816,0.009828316,0.3190957,0.009381205,0.00005079972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1434004,0.0009899967,0.8155123,0.004345331,0.0002200202,0.0002170936,0.0003306089,0.003276045,0.0317082],"genre_scores_gemma":[0.9536771,0.000342079,0.04075002,0.0008645577,0.00006189913,0.0001373789,0.0002196698,0.0002343264,0.003713092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004382586,"threshold_uncertainty_score":0.01483291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06371097362501402,"score_gpt":0.2000806973805253,"score_spread":0.1363697237555112,"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."}}