Repository logo
 
Publication

A deep learning-based taphonomical approach to distinguish the modifying agent in the late pleistocene site of toll cave (Barcelona, Spain)

2023Journal article Restricted access
Simple item page
dc.contributor.authorPizarro-Monzo, Marcos
dc.contributor.authorRosell, Jordi
dc.contributor.authorRufà, Anna
dc.contributor.authorRivals, Florent
dc.contributor.authorBlasco, Ruth
dc.date.accessioned2023-10-11T13:31:07Z
dc.date.available2023-10-11T13:31:07Z
dc.date.issued2023
dc.description.abstractOne of the most widely used methods to associate lithic tools and bone assemblage in archaeological sites is the identification of cut-marks. However, the identification of these marks is still problematic in some localities on account of the similarities with the modifications generated by non-human processes, including biostratinomic and post-depositional bone surface modifications. Toll Cave (Barcelona, Spain), with chronologies between 47.310 BP and 69.800 BP, is one of the case studies where the cut-marks could easily be confused with abundant grooves generated by the dragging of sedimentary particles (e.g. trampling), but also with the scores produced by carnivores. In this work, we present the results obtained from applying Deep Learning (DL) models to the taphonomic analysis of the site. This methodological approach has allowed us to distinguish the bone surface modifications with 97.5% reliability. We show the usefulness of this technique to help solve many taphonomic equifinality problems in the archaeological assemblages, as well as the need to implement new approaches to eliminate subjectivity in the descriptions of bone damage and make more accurate inferences about the past.pt_PT
dc.description.sponsorshipPID2019-103987GB-C31; PID2022-138590NB-C41; CLT009/22/000045, 2021 SGR 01238 and 2021 SGR 01239 ; RYC2019-026386-I; PID2020-114462GB-I00; CEX2019-000945-Mpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1080/08912963.2023.2242370pt_PT
dc.identifier.issn0891-2963
dc.identifier.urihttp://hdl.handle.net/10400.1/20036
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherTaylor and Francispt_PT
dc.relationSearching for the lost pieces: unravelling the role of small game in the Iberian Palaeolithic
dc.subjectDeep Learning (DL)pt_PT
dc.subjectCut markspt_PT
dc.subjectScorespt_PT
dc.subjectTramplingpt_PT
dc.subjectToll Cavept_PT
dc.subjectLate Pleistocenept_PT
dc.titleA deep learning-based taphonomical approach to distinguish the modifying agent in the late pleistocene site of toll cave (Barcelona, Spain)pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleSearching for the lost pieces: unravelling the role of small game in the Iberian Palaeolithic
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC IND 3ed/2020.00877.CEECIND%2FCP1613%2FCT0003/PT
oaire.citation.endPage10pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleHistorical Biologypt_PT
oaire.fundingStreamCEEC IND 3ed
person.familyNameRufà
person.givenNameAnna
person.identifier.ciencia-id181D-DDA5-2D9E
person.identifier.orcid0000-0003-1278-4220
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationbf3e3984-e144-45b8-9514-4a3e2d3a5ee1
relation.isAuthorOfPublication.latestForDiscoverybf3e3984-e144-45b8-9514-4a3e2d3a5ee1
relation.isProjectOfPublicationb5d02dce-11b4-4310-bef4-4a47894eb43f
relation.isProjectOfPublication.latestForDiscoveryb5d02dce-11b4-4310-bef4-4a47894eb43f

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
A deep learning-based taphonomical approach to distinguish the modifying agent in the Late Pleistocene site of Toll Cave Barcelona Spain .pdf
Size:
8.89 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
3.46 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ICR2-Artigos (em revistas ou actas indexadas)