Evidence map›Paper›PMID 35774636›Full record

ArticleFrontiers in artificial intelligence2022

An Analysis of Music Perception Skills on Crowdsourcing Platforms.

Ioannis Petros Samiotis, Sihang Qiu, Christoph Lofi, Jie Yang, Ujwal Gadiraju, Alessandro Bozzon

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2022. 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

6 authors.

Ioannis Petros SamiotisDepartment of Software Technology, Delft University of Technology, Delft, Netherlands.
Sihang QiuDepartment of Software Technology, Delft University of Technology, Delft, Netherlands.
Christoph LofiDepartment of Software Technology, Delft University of Technology, Delft, Netherlands.
Jie YangDepartment of Software Technology, Delft University of Technology, Delft, Netherlands.
Ujwal GadirajuDepartment of Software Technology, Delft University of Technology, Delft, Netherlands.
Alessandro BozzonDepartment of Software Technology, Delft University of Technology, Delft, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Music content annotation campaigns are common on paid crowdsourcing platforms. Crowd workers are expected to annotate complex music artifacts, a task often demanding specialized skills and expertise, thus selecting the right participants is crucial for campaign success. However, there is a general lack of deeper understanding of the distribution of musical skills, and especially auditory perception skills, in the worker population. To address this knowledge gap, we conducted a user study (

Indexed as

human computationknowledge crowdsourcingmusic annotationmusic sophisticationperceptual skills

Identifiers

PMID35774636
PMCPMC9237482

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.