Evidence map›Paper›PMID 39729478›Full record

Trial reportPloS one2024

A randomized controlled trial on anonymizing reviewers to each other in peer review discussions.

Charvi Rastogi, Xiangchen Song, Zhijing Jin, Ivan Stelmakh, Hal Daumé, Kun Zhang, Nihar B Shah

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

7 authors.

Charvi RastogiMachine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
Xiangchen SongMachine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
Zhijing JinComputer Science Department, ETH Zürich, Zürich, Switzerland.
Ivan StelmakhNew Economic School, Moscow, Russia.
Hal DauméDepartment of Computer Science, University of Maryland, College Park, Maryland, United States of America.
Kun ZhangPhilosophy Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
Nihar B ShahMachine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.ORCID 0000-0001-5158-9677

Funding

Interpretable graphical models for large multi-modal COPD data (R01HL159805)R01HL159805 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BENOS, PANAGIOTIS V, SPIRTES, PETER · 2021 to 2024
$2.0M
NHLBI NIH HHS R01 HL159805
6 · The paper itself

Abstract

Many peer-review processes involve reviewers submitting their independent reviews, followed by a discussion between the reviewers of each paper. A common question among policymakers is whether the reviewers of a paper should be anonymous to each other during the discussion. We shed light on this question by conducting a randomized controlled trial at the Conference on Uncertainty in Artificial Intelligence (UAI) 2022 conference where reviewer discussions were conducted over a typed forum. We randomly split the reviewers and papers into two conditions-one with anonymous discussions and the other with non-anonymous discussions. We also conduct an anonymous survey of all reviewers to understand their experience and opinions. We compare the two conditions in terms of the amount of discussion, influence of seniority on the final decisions, politeness, reviewers' self-reported experiences and preferences. Overall, this experiment finds small, significant differences favoring the anonymous discussion setup based on the evaluation criteria considered in this work.

Indexed as

Peer Review, ResearchArtificial IntelligenceHumansSurveys and Questionnaires

Identifiers

PMID39729478
PMCPMC11676492

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.