Evidence map›Paper›PMID 28704414›Full record

ArticlePloS one2017

Examining the use of Amazon's Mechanical Turk for edge extraction of the occlusal surface of fossilized bovid teeth.

Gregory J Matthews, George K Thiruvathukal, Maxwell P Luetkemeier, Juliet K Brophy

Abstract read
In one paragraph

Article in PloS one, 2017. 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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Gregory J MatthewsDepartment of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, United States of America.ORCID http://orcid.org/0000-0002-8413-5097
George K ThiruvathukalDepartment of Computer Science, Loyola University Chicago, Chicago, IL, United States of America.
Maxwell P LuetkemeierDepartment of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, United States of America.
Juliet K BrophyDepartment of Geography and Anthropology, Louisiana State University, Baton Rouge, LA, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to reconstruct environments associated with Plio-Pleistocene hominins in southern Africa, researchers frequently rely upon the animals associated with the hominins, in particular, animals in the Family Bovidae. Bovids in southern Africa are typically identified by their teeth. However, identifying the taxon of a bovid tooth is challenging due to various biasing factors. Furthermore, inaccurate identification of fossil bovids can have significant consequences on the reconstructed paleoenvironment. Recent research on the classification of bovid fossil teeth has relied on using elliptical Fourier analysis to summarize the shape of the outline of the occlusal surface of the tooth and the resulting harmonic amplitudes. Currently, an expert in the field must manually place landmarks around the edges of each tooth which is slow and time consuming. This study tests whether it is possible to crowdsource this task, while maintaining the necessary level of quality needed to perform a statistical analysis on each tooth. Amazon Mechanical Turk workers place landmarks on the edge of the tooth which is compared to the performance of an expert in the field. The results suggest that crowdsourcing the digitization process is reliable and replicable. With the technical aspects of digitization managed, researchers can concentrate on analyzing and interpreting the data.

Indexed as

AnimalsCattleCrowdsourcingData CollectionFossilsTooth

Identifiers

PMID28704414
PMCPMC5509114

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LicenceCC BY
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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.