Polish is quantitatively different on quartzite flakes used on different worked materials
- Publikationstyp:
- Zeitschriftenaufsatz
- Metadaten:
-
- Autoren
- Antonella Pedergnana
- Ivan Calandra
- Adrian A Evans
- Konstantin Bob
- Andreas Hildebrandt
- Andreu Olle
- Autoren-URL
- https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000597149100158&DestLinkType=FullRecord&DestApp=WOS_CPL
- DOI
- 10.1371/journal.pone.0243295
- Externe Identifier
- Clarivate Analytics Document Solution ID: PC7AH
- PubMed Identifier: 33270795
- ISSN
- 1932-6203
- Ausgabe der Veröffentlichung
- 12
- Zeitschrift
- PLOS ONE
- Artikelnummer
- ARTN e0243295
- Datum der Veröffentlichung
- 2020
- Status
- Published
- Titel
- Polish is quantitatively different on quartzite flakes used on different worked materials
- Sub types
- Article
- Ausgabe der Zeitschrift
- 15
Datenquelle: Web of Science (Lite)
- Andere Metadatenquellen:
-
- Abstract
- <jats:p>Metrology has been successfully used in the last decade to quantify use-wear on stone tools. Such techniques have been mostly applied to fine-grained rocks (chert), while studies on coarse-grained raw materials have been relatively infrequent. In this study, confocal microscopy was employed to investigate polished surfaces on a coarse-grained lithology, quartzite. Wear originating from contact with five different worked materials were classified in a data-driven approach using machine learning. Two different classifiers, a decision tree and a support-vector machine, were used to assign the different textures to a worked material based on a selected number of parameters (<jats:italic>Mean density of furrows</jats:italic>,<jats:italic>Mean depth of furrows</jats:italic>,<jats:italic>Core material volume-Vmc</jats:italic>). The method proved successful, presenting high scores for bone and hide (100%). The obtained classification rates are satisfactory for the other worked materials, with the only exception of cane, which shows overlaps with other materials. Although the results presented here are preliminary, they can be used to develop future studies on quartzite including enlarged sample sizes.</jats:p>
- Autoren
- Antonella Pedergnana
- Ivan Calandra
- Adrian A Evans
- Konstantin Bob
- Andreas Hildebrandt
- Andreu Ollé
- DOI
- 10.1371/journal.pone.0243295
- Editoren
- Marco Peresani
- eISSN
- 1932-6203
- Ausgabe der Veröffentlichung
- 12
- Zeitschrift
- PLOS ONE
- Sprache
- en
- Online publication date
- 2020
- Paginierung
- e0243295 - e0243295
- Status
- Published online
- Herausgeber
- Public Library of Science (PLoS)
- Herausgeber URL
- http://dx.doi.org/10.1371/journal.pone.0243295
- Datum der Datenerfassung
- 2021
- Titel
- Polish is quantitatively different on quartzite flakes used on different worked materials
- Ausgabe der Zeitschrift
- 15
Datenquelle: Crossref
- Abstract
- Metrology has been successfully used in the last decade to quantify use-wear on stone tools. Such techniques have been mostly applied to fine-grained rocks (chert), while studies on coarse-grained raw materials have been relatively infrequent. In this study, confocal microscopy was employed to investigate polished surfaces on a coarse-grained lithology, quartzite. Wear originating from contact with five different worked materials were classified in a data-driven approach using machine learning. Two different classifiers, a decision tree and a support-vector machine, were used to assign the different textures to a worked material based on a selected number of parameters (Mean density of furrows, Mean depth of furrows, Core material volume-Vmc). The method proved successful, presenting high scores for bone and hide (100%). The obtained classification rates are satisfactory for the other worked materials, with the only exception of cane, which shows overlaps with other materials. Although the results presented here are preliminary, they can be used to develop future studies on quartzite including enlarged sample sizes.
- Addresses
- TraCEr, Laboratory for Traceology and Controlled Experiments at MONREPOS Archaeological Research Centre and Museum for Human Behavioural Evolution, RGZM, Neuwied, Germany.
- Autoren
- Antonella Pedergnana
- Ivan Calandra
- Adrian A Evans
- Konstantin Bob
- Andreas Hildebrandt
- Andreu Ollé
- DOI
- 10.1371/journal.pone.0243295
- eISSN
- 1932-6203
- Externe Identifier
- PubMed Identifier: 33270795
- PubMed Central ID: PMC7714215
- Funding acknowledgements
- Universitat Rovira i Virgili: 2019-PFR-URV-91
- AGAUR: 2017-SGR-1040
- Arts and Humanities Research Council: AH/L00688X/1
- MICINU-FEDER: PGC2018-093925-B-C32
- Leibniz-Gemeinschaft: Sondertatbestand “Spurenlabor”
- Open access
- true
- ISSN
- 1932-6203
- Ausgabe der Veröffentlichung
- 12
- Zeitschrift
- PloS one
- Schlüsselwörter
- Quartz
- Sprache
- eng
- Medium
- Electronic-eCollection
- Online publication date
- 2020
- Open access status
- Open Access
- Paginierung
- e0243295
- Datum der Veröffentlichung
- 2020
- Status
- Published
- Publisher licence
- CC BY
- Datum der Datenerfassung
- 2020
- Titel
- Polish is quantitatively different on quartzite flakes used on different worked materials.
- Sub types
- Research Support, Non-U.S. Gov't
- research-article
- Journal Article
- Ausgabe der Zeitschrift
- 15
Files
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0243295&type=printable https://europepmc.org/articles/PMC7714215?pdf=render
Datenquelle: Europe PubMed Central
- Abstract
- Metrology has been successfully used in the last decade to quantify use-wear on stone tools. Such techniques have been mostly applied to fine-grained rocks (chert), while studies on coarse-grained raw materials have been relatively infrequent. In this study, confocal microscopy was employed to investigate polished surfaces on a coarse-grained lithology, quartzite. Wear originating from contact with five different worked materials were classified in a data-driven approach using machine learning. Two different classifiers, a decision tree and a support-vector machine, were used to assign the different textures to a worked material based on a selected number of parameters (Mean density of furrows, Mean depth of furrows, Core material volume-Vmc). The method proved successful, presenting high scores for bone and hide (100%). The obtained classification rates are satisfactory for the other worked materials, with the only exception of cane, which shows overlaps with other materials. Although the results presented here are preliminary, they can be used to develop future studies on quartzite including enlarged sample sizes.
- Date of acceptance
- 2020
- Autoren
- Antonella Pedergnana
- Ivan Calandra
- Adrian A Evans
- Konstantin Bob
- Andreas Hildebrandt
- Andreu Ollé
- Autoren-URL
- https://www.ncbi.nlm.nih.gov/pubmed/33270795
- DOI
- 10.1371/journal.pone.0243295
- eISSN
- 1932-6203
- Externe Identifier
- PubMed Central ID: PMC7714215
- Ausgabe der Veröffentlichung
- 12
- Zeitschrift
- PLoS One
- Schlüsselwörter
- Quartz
- Sprache
- eng
- Country
- United States
- Paginierung
- e0243295
- PII
- PONE-D-20-26826
- Datum der Veröffentlichung
- 2020
- Status
- Published online
- Datum, an dem der Datensatz öffentlich gemacht wurde
- 2021
- Titel
- Polish is quantitatively different on quartzite flakes used on different worked materials.
- Sub types
- Journal Article
- Research Support, Non-U.S. Gov't
- Ausgabe der Zeitschrift
- 15
Datenquelle: PubMed
- Beziehungen:
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