Evidence map›Paper›PMID 42035165›Full record

ArticleTrials2026

Enhancing the scope of the Trials to Publications tool by identifying ClinicalTrial.gov registry mentions in full-text.

Arthur W Holt, Neil R Smalheiser

Abstract read
In one paragraph

Article in Trials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Arthur W HoltDepartment of Psychiatry, University of Illinois at Chicago, Chicago, IL, 60612, USA.
Neil R SmalheiserDepartment of Psychiatry, University of Illinois at Chicago, Chicago, IL, 60612, USA. neils@uic.edu.

Funding

Automated Indexing for Publication Types and Study DesignsR01LM014292 · NLM · UNIVERSITY OF ILLINOIS AT CHICAGO · PI SMALHEISER, NEIL R · 2023 to 2025
$948k
NLM NIH HHS R01 LM014292U.S. National Library of Medicine 1R01LM014292-01
6 · The paper itself

Abstract

We have previously described a free, public web-based tool, Trials to Publications, https://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/TrialPubLinking/trial_pub_link_start.cgi , which employs a machine-learning model based on title, abstract, and other metadata features to predict which publications are likely to present clinical outcome results from a given registered trial in ClinicalTrials.gov. We have now updated and expanded the scope of the tool, by extracting mentions of ClinicalTrials.gov registry numbers (NCT numbers) from the full-text of 3 online biomedical article collections (open access PubMed Central (PMC), EuroPMC, and OpenAlex), as well as retrieving biomedical publications that are mentioned within the ClinicalTrials.gov registry itself. These mentions greatly increase the number of linked publications identified by the tool and should assist those carrying out evidence syntheses as well as those studying the metascience of clinical trials.

Indexed as

Clinical Trials as TopicData MiningInformation Storage and RetrievalRegistriesHumansMachine LearningBibliographic databasesClinical trialsInformation retrievalLinking trials to publicationsSystematic reviews

Identifiers

PMID42035165
PMCPMC13248297

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.