{"id":"W4399759465","doi":"10.48550/arxiv.2406.10161","title":"On the Computability of Robust PAC Learning","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computability; Computer science; Artificial intelligence; Mathematics education; Mathematics; Theoretical computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006525768,0.0002440063,0.0002822247,0.0001529994,0.0001629597,0.0001120868,0.001633304,0.0001566259,0.00004868668],"category_scores_gemma":[0.0001234246,0.0001949961,0.0002532234,0.0005469351,0.0001351543,0.000054005,0.00293731,0.001865237,0.0001211939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008241105,"about_ca_system_score_gemma":0.0001254273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001825191,"about_ca_topic_score_gemma":0.000006214358,"domain_scores_codex":[0.9981888,0.0004035074,0.0001755571,0.0008720167,0.0001242631,0.0002358412],"domain_scores_gemma":[0.9980518,0.000537859,0.0001949368,0.001044356,0.00009478282,0.00007629656],"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":[0.000004665249,0.00003652354,0.0005481376,0.000073448,0.00004014244,0.00004447754,0.0002143377,0.6996714,0.000002557917,0.2980012,0.0001895768,0.001173552],"study_design_scores_gemma":[0.00008231754,0.00006600507,0.0005359841,0.0001349215,0.00002489453,0.00000168481,0.00004310513,0.8870198,0.00002794558,0.1115803,0.0002980497,0.000185038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4678949,0.00006898852,0.5207894,0.0007827142,0.0008326846,0.0002053731,0.000006422048,0.0003926576,0.009026873],"genre_scores_gemma":[0.9970844,0.00001860553,0.0008569867,0.00005472832,0.00006328882,4.057994e-7,0.000003616814,0.00001356497,0.001904437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5291895,"threshold_uncertainty_score":0.810363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06114499898615442,"score_gpt":0.1842416270676044,"score_spread":0.12309662808145,"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."}}