Pith. Sign in

RECORD

Upper Limits in the Case That Zero Events are Observed: An Intuitive Solution to the Background Dependence Puzzle

PaperPDF from arXiv

data files

Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
X Bluesky LinkedIn Reddit Hacker News
P. Astone, G. Pizzella

High Energy Physics - Experiment · Submitted 10 Feb 2000

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim On the other hand, the Bayesian approach leads to a result which is background independent.

how it is stated · asserted 1.00 read the record →

Comment (0) Read on arXiv ↗
Cite ▾
arXiv IDhep-ex/0002028 (version 1)
Pith IDBUAY456G, Pith's permanent record of this paper and its review
CitationG. Pizzella, P. Astone. "Upper Limits in the Case That Zero Events are Observed: An Intuitive Solution to the Background Dependence Puzzle." arXiv:hep-ex/0002028 (2000). https://pith.science/paper/BUAY456G
Claim paper

The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Open the compiled record

Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,565 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.25 · human participants 0.02 · controlled comparison 0.13 · randomized assignment 0.01 · states quantitative result 0.09 · compares with prior results 0.95 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

We compare the ``unified approach'' for the estimation of upper limits with an approach based on the Bayes theory, in the special case that no events are observed. The ``unified approach'' predicts, in this case, an upper limit that decreases with the increase in the expected level of background. This seems absurd. On the other hand, the Bayesian approach leads to a result which is background independent. An explanation of the Bayesian result is presented, together with suggested reasons for the paradoxical result of the ``unified approach''.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We compare the ``unified approach'' for the estimation of upper limits with an approach based on the Bayes theory, in the special case that no events are observed. contribution 0.88 0.82 0.05 asserted 0.95
s1 The ``unified approach'' predicts, in this case, an upper limit that decreases with the increase in the expected level of background. This seems absurd. result 0.68 0.30 0.17 asserted 0.99
s2 On the other hand, the Bayesian approach leads to a result which is background independent. result 0.99 0.34 0.31 asserted 1.00
s3 An explanation of the Bayesian result is presented, together with suggested reasons for the paradoxical result of the ``unified approach''. contribution 0.60 0.85 0.16 asserted 0.79

What kind of paper the classifier reports this is: position or commentary 0.82 · evidence from argument 0.79.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We compare the ``unified approach'' for the estimation of upper limits with an approach based on the Bayes theory, in the special case that no events are observed. The ``unified approach'' predicts, in this case, an upper limit that decreases with the increase in the expected level of background. This seems absurd. On the other hand, the Bayesian approach leads to a result which is background independent. An explanation of the Bayesian result is presented, together with suggested reasons for the paradoxical result of the ``unified approach''.

Human review

How Pith checks papers → · Full audit of this paper →

References
How the literature uses it

1 arXiv paper cite this in 1 sentence

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it

Uses its method or tool 1 paper

Discussion

Know something about this paper? Leave a comment, or highlight any passage above to comment on it.