Evidence map›Paper›PMID 29911205›Full record

ArticleLREC ... International Conference on Language Resources & Evaluation : [proceedings]. International Conference on Language Resources & Evaluation2018

Three Dimensions of Reproducibility in Natural Language Processing.

K Bretonnel Cohen, Jingbo Xia, Pierre Zweigenbaum, Tiffany J Callahan, Orin Hargraves, Foster Goss, Nancy Ide, Aurélie Névéol, Cyril Grouin, Lawrence E Hunter

Abstract read
In one paragraph

Article in LREC ... International Conference on Language Resources & Evaluation : [proceedings]. International Conference on Language Resources & Evaluation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Reproducibility of social science research using aggregate statistics with noise infused for differential privacy.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Article
  4. TRESTLE: Toolkit for Reproducible Execution of Speech, Text and Language Experiments.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
  5. Can reproducibility be improved in clinical natural language processing? A study of 7 clinical NLP suites.Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

K Bretonnel CohenComputational Bioscience Program, University of Colorado School of Medicine.
Jingbo XiaHuazhong Agricultural University.
Pierre ZweigenbaumLIMSI, CNRS, Université Paris-Saclay.
Tiffany J CallahanComputational Bioscience Program, University of Colorado School of Medicine.
Orin HargravesUniversity of Colorado Boulder.
Foster GossDepartment of Emergency Medicine, University of Colorado.
Nancy IdeVassar College.
Aurélie NévéolLIMSI, CNRS, Université Paris-Saclay.
Cyril GrouinLIMSI, CNRS, Université Paris-Saclay.
Lawrence E HunterComputational Bioscience Program, University of Colorado School of Medicine.

Funding

Computational Bioscience Program Training GrantT15LM009451 · NLM · UNIVERSITY OF COLORADO DENVER · PI Katherina Kechris-Mays, Arjun Krishnan · 2007 to 2026
$11.7M
Technology Development for a MolBio Knowledge-BaseR01LM008111 · NLM · UNIVERSITY OF COLORADO DENVER · PI HUNTER, LAWRENCE E · 2004 to 2021
$9.7M
Bio Text NLPR01LM009254 · NLM · UNIVERSITY OF COLORADO DENVER · PI HUNTER, LAWRENCE E · 2006 to 2018
$5.9M
NLP to Identify and Rank Clinically Relevant Information for EHRs in the Emergency DepartmentR21HS024541 · AHRQ · UNIVERSITY OF COLORADO DENVER · PI GOSS, FOSTER R · 2016 to 2017
$298k
AHRQ HHS R21 HS024541NLM NIH HHS R01 LM008111NLM NIH HHS R01 LM009254NLM NIH HHS T15 LM009451
6 · The paper itself

Abstract

Despite considerable recent attention to problems with reproducibility of scientific research, there is a striking lack of agreement about the definition of the term. That is a problem, because the lack of a consensus definition makes it difficult to compare studies of reproducibility, and thus to have even a broad overview of the state of the issue in natural language processing. This paper proposes an ontology of reproducibility in that field. Its goal is to enhance both future research and communication about the topic, and retrospective meta-analyses. We show that three dimensions of reproducibility, corresponding to three kinds of claims in natural language processing papers, can account for a variety of types of research reports. These dimensions are reproducibility of a

Indexed as

methodologyrepeatabilityreplicabilityreplicatabilityreproducibility

Identifiers

PMID29911205
PMCPMC5998676

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.