{"id":"W2912789966","doi":"10.48550/arxiv.1902.02459","title":"On Mean Estimation for General Norms with Statistical Queries","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Normed vector space; Distribution (mathematics); Combinatorics; Oracle; Norm (philosophy); Mathematics; Space (punctuation); Discrete mathematics; Computer science; Mathematical analysis","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000139005,0.0002622847,0.0002792057,0.0001829869,0.0001659955,0.0001529995,0.0009957448,0.0001432245,0.00001732035],"category_scores_gemma":[0.00002523272,0.0002495449,0.0001060802,0.0002393224,0.0001414487,0.0002590333,0.0005804294,0.0003247869,0.00003847044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001151775,"about_ca_system_score_gemma":0.0001703553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009375236,"about_ca_topic_score_gemma":0.00006962137,"domain_scores_codex":[0.9985408,0.00005372869,0.0001347061,0.0008717276,0.0001134808,0.0002855558],"domain_scores_gemma":[0.9984891,0.000257075,0.0001457551,0.0008748622,0.0001299866,0.0001032195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005639669,0.00004641975,0.0001144459,0.00005781067,0.0000373349,0.00002861192,0.0001005498,0.2770088,9.735181e-7,0.721036,0.000221692,0.001291035],"study_design_scores_gemma":[0.0003575029,0.0002168101,0.0005060439,0.00005033246,0.00002392095,0.000002318087,0.00001139295,0.6857917,0.00003328183,0.3125909,0.0001583271,0.0002574841],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07358839,0.000005293667,0.9243467,0.00007621157,0.0004545061,0.0004151766,0.00008504989,0.0001580588,0.0008706363],"genre_scores_gemma":[0.8428308,0.000008995662,0.1559952,0.0001051858,0.00005046221,0.000002817237,0.00007761275,0.00001490252,0.0009139678],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7692425,"threshold_uncertainty_score":0.9999957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06122917284165266,"score_gpt":0.2007774211881723,"score_spread":0.1395482483465197,"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."}}