Evidence map›Paper›PMID 38598482›Full record

ArticlePloS one2024

How do authors' perceptions of their papers compare with co-authors' perceptions and peer-review decisions?

Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé Iii, Emma Pierson, Nihar B Shah

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Charvi RastogiMachine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.ORCID 0000-0003-0820-4115
Ivan StelmakhNew Economic School, Moscow, Russia.
Alina BeygelzimerYahoo! Research, New York, New York, United States of America.
Yann N DauphinGoogle Deepmind, Montreal, Canada.
Percy LiangDepartment of Computer Science, Stanford University, Stanford, California, United States of America.
Jennifer Wortman VaughanMicrosoft Research, New York, New York, United States of America.
Zhenyu XueIndependent Researcher, Shanghai, China.
Hal Daumé IiiDepartment of Computer Science, University of Maryland, College Park, Maryland, United States of America.
Emma PiersonJacobs Technion-Cornell Institute, Cornell Tech, New York, New York, United States of America.
Nihar B ShahMachine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.ORCID 0000-0001-5158-9677

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

How do author perceptions match up to the outcomes of the peer-review process and perceptions of others? In a top-tier computer science conference (NeurIPS 2021) with more than 23,000 submitting authors and 9,000 submitted papers, we surveyed the authors on three questions: (i) their predicted probability of acceptance for each of their papers, (ii) their perceived ranking of their own papers based on scientific contribution, and (iii) the change in their perception about their own papers after seeing the reviews. The salient results are: (1) Authors had roughly a three-fold overestimate of the acceptance probability of their papers: The median prediction was 70% for an approximately 25% acceptance rate. (2) Female authors exhibited a marginally higher (statistically significant) miscalibration than male authors; predictions of authors invited to serve as meta-reviewers or reviewers were similarly calibrated, but better than authors who were not invited to review. (3) Authors' relative ranking of scientific contribution of two submissions they made generally agreed with their predicted acceptance probabilities (93% agreement), but there was a notable 7% responses where authors predicted a worse outcome for their better paper. (4) The author-provided rankings disagreed with the peer-review decisions about a third of the time; when co-authors ranked their jointly authored papers, co-authors disagreed at a similar rate-about a third of the time. (5) At least 30% of respondents of both accepted and rejected papers said that their perception of their own paper improved after the review process. The stakeholders in peer review should take these findings into account in setting their expectations from peer review.

Indexed as

Peer ReviewPeer Review, ResearchFemaleHumansMaleSurveys and Questionnaires

Identifiers

PMID38598482
PMCPMC11006147

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.