Evidence map›Paper›PMID 32612800›Full record

Articlei-Perception

MILO Mobile: An iPad App to Measure Search Performance in Multi-Target Sequences.

Ian M Thornton, Todd S Horowitz

Abstract read
In one paragraph

Article in i-Perception. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

2 authors.

Ian M ThorntonDepartment of Cognitive Science, Faculty of Media and Knowledge Sciences, University of Malta.ORCID https://orcid.org/0000-0001-6328-3536
Todd S HorowitzNational Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article introduces a mobile app version of the Multi-Item Localization (MILO) task. The MILO task was designed to explore the temporal context of search through a sequence and has proven useful in both basic and applied research settings. Here, we describe the basic features of the app and how it can be obtained, installed, and modified. We also provide example data files and present two new sets of empirical data to verify that previous findings concerning prospective planning and retrospective memory (i.e., inhibitory tagging) are reproducible with the app. We conclude by discussing ongoing studies and future modifications that illustrate the flexibility and potential of the MILO Mobile app.

Indexed as

actionattentionmemoryvisual search

Identifiers

PMID32612800
PMCPMC7307404

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.