{"arxiv_id":"hep-ph/0501067","title":"Unbiased determination of the proton structure function F_2^p with faithful uncertainty estimation","abstract":"We construct a parametrization of the deep-inelastic structure function of the proton F_2 based on all available experimental information from charged lepton deep-inelastic scattering experiments. The parametrization effectively provides a bias-free determination of the probability measure in the space of structure functions, which retains information on experimental errors and correlations. The result is obtained in the form of a Monte Carlo sample of neural networks trained on an ensemble of replicas of the experimental data. We discuss in detail the techniques required for the construction of bias-free parameterizations of large amounts of structure function data, in view of future applications to the determination of parton distributions based on the same method.","primary_cat":"hep-ph","cross_cats":[],"submitted_at":"2005-01-09T20:46:02+00:00","latest_version":2,"source":"arxiv","source_label":"arXiv","source_url":null,"has_pdf":true,"has_source":false,"verdict":"CONDITIONAL","confidence":"HIGH","one_line_summary":"A Monte Carlo ensemble of 1000 neural networks, trained on replicas of all charged-lepton DIS data, yields a bias-free F2(x,Q2) with a faithful uncertainty band.","novelty_score":5.0,"correctness_risk":"medium","formal_verification":"none","upvotes":0,"downvotes":0,"pith_score":0.0,"inbound_count":33,"_links":{"html":"https://pith.science/paper/hep-ph/0501067","verdict":"/api/v1/verdicts/hep-ph/0501067"}}