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M\'etodo de Regularizaci\'on para Identificar una Fuente en una Ecuaci\'on El\'iptica

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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Guillermo Federico Umbricht, Diana Rubio

Analysis of PDEs · Submitted 2 Nov 2021

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

The authors' main claim After analyzing the results some considerations on its effective implementation are discussed.

how it is stated · asserted 0.69 read the record →

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arXiv ID2111.01736 (version 1)
Pith IDIMEC3OFS, Pith's permanent record of this paper and its review
CitationDiana Rubio, Guillermo Federico Umbricht. "M\'etodo de Regularizaci\'on para Identificar una Fuente en una Ecuaci\'on El\'iptica." arXiv:2111.01736 (2021). https://pith.science/paper/IMEC3OFS
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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.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,195 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.17 · human participants 0.02 · controlled comparison 0.06 · randomized assignment 0.01 · states quantitative result 0.05 · compares with prior results 0.07 · mentions code or data availability 0.02.

The abstract, sentence by sentence

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

The aim of this paper is to numerically study the performance of a method of regularization. This technique was developed to solve the illposed problem of estimating a source-dimensional Poisson equation for two dimensions from measurements taken over a line inside the domain. The proposed method consists in adding a regularization term to the equation that depends on a parameter, which is called regularization parameter. In this paper we show the results for different values of this parameter as well as for different levels of noise in the data used for estimation. After analyzing the results some considerations on its effective implementation are discussed.

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 The aim of this paper is to numerically study the performance of a method of regularization. contribution 0.97 0.56 0.03 asserted 0.80
s1 This technique was developed to solve the illposed problem of estimating a source-dimensional Poisson equation for two dimensions from measurements taken over a line inside the domain. background 0.75 0.17 0.04 asserted 1.00
s2 The proposed method consists in adding a regularization term to the equation that depends on a parameter, which is called regularization parameter. method 0.99 0.43 0.03 asserted 1.00
s3 In this paper we show the results for different values of this parameter as well as for different levels of noise in the data used for estimation. contribution 0.53 0.93 0.07 asserted 1.00
s4 After analyzing the results some considerations on its effective implementation are discussed. interpretation 0.83 0.68 0.10 asserted 0.69

What kind of paper the classifier reports this is: simulation study 0.82 · evidence from simulation or computation 1.00.

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

The aim of this paper is to numerically study the performance of a method of regularization. This technique was developed to solve the illposed problem of estimating a source-dimensional Poisson equation for two dimensions from measurements taken over a line inside the domain. The proposed method consists in adding a regularization term to the equation that depends on a parameter, which is called regularization parameter. In this paper we show the results for different values of this parameter as well as for different levels of noise in the data used for estimation. After analyzing the results some considerations on its effective implementation are discussed.

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