The Dead Sea Roles are one of the most important troves of religious Manuscripts ever found, with many the oldest surviving copies of Biblical texts.
Found for the first time by a Bedoein Herder, the hundreds of old rolls – were excavated from the Qumran caves, on the West Bank, between 1946 and 1956 – a blessing for those who study the history of Judaism and Christianity.
But although we know that the roles are all between 2,500 and 1,800 years old, only a fracture dates have written that indicate when they were first composed.
Funing the age of the other roles can help scientists understand how Judaism has evolved and which scripts and ideas were important at different times.
Now an international team of researchers has focused on filling a few gaps in the timeline of the Dead Sea roles using a combination of artificial intelligence (AI), carbon dating and manuscript analysis.
In the diary Plos OneThey presented new ages for more than 100 scroll fragments and found many older than before.
The Dead Sea roles were found in pots in the Qumran caves, now on the western Jordoever. ((Flickr: Lux Moundi / CC by 2.0))
Gareth Wearne, a researcher in Bible studies and the history of ancient Israel of Australian Catholic University, said that the research could change our understanding of the history of the Dead Sea Roles.
“It may have consequences for how we think about how the material was copied and spread at the start of the process that eventually led them to be included in the Biblical Canon,” Dr. Wearne, who was not involved in the study.
The dangers of carbon dating
Radio cabbage dating is often invoked in archeology to find the age of an artifact, and the Dead Sea Rolls are no exception.
But the technology is vulnerable to contamination and often produces inaccurate results, especially for the period in which the Dead Sea roles were written: there are fewer artifacts with known data to calibrate the age of the roles.
In addition, as the archaeologist of the University of Groningen and study author Mladen Popović noted: “Radio harbon dating is a destructive method”.
Researchers now only need a few thousandth gram material to give carbon, but artifacts with the cultural importance of the dead sea rolls are incredibly expensive.
Most Dead Sea -Roles are written in Hebrew, but some are in Aramaic, Greek, Latin and Arabic. ((Leveld: US Library of Congress/Matson Photo Service))
Another common technique that is used to study the roles is paleography, or the study of handwriting, which looks at the way in which scripts have changed over the centuries.
But this method is also vulnerable to inaccuracies.
So researchers such as Professor Popović and his colleagues have searched for ways to date the roles when other methods fail.
In their new studies, the teamcool of the team of 24 Dead Sea Shift samples.
The researchers gave digital images of the 24 dated roles in a machine learning model – a type AI – that is designed to analyze the handwriting in the roles.
Subsequently, the AI had predicted the age of 135 other roles, based on their handwriting and scripts.
“AI analysis of the digital images of the roles does not destroy them”, “
Professor Popovic said.
The researchers mentioned their AI model Enoch, depicted after a figure in the book Genesis that they considered a “science hero”.
Revision of the history of the Dead Sea scroll
The predictions of Enoch, and the carbon dated samples, found that many of the roles were older than before – sometimes against decades, sometimes in a few years.
The study suggested that two of the Dead Sea roles may be texts that are contemporary when they were first written, or close by.
One Scroll, which contains a fragment from the book Daniel, was carbon dated to between 230 and 160 BC – up to 100 years older than previous estimates.
This means that it overlaps with when the text was considered written, based on historical events that it refers to.
Scholars use historical events that are referred to in biblical texts to determine when they may have been written. ((Commons Wikimedia: Osama Shikir Muhammed Amin / CCE by-SA 4.0))
Another Scroll, which contained text by preacher, was dated with the Enoch Ai until the third century BC.
The text had previously thought that it had been made in the middle of the second century BC Based on how it was in accordance with the cultural movements of the era.
If the dating is correct, these two fragments would be the first known examples of biblical texts from the moment the work was compiled.
Expert Paleographers checked the results of the AI and found 79 percent of them realistic predictions.
AI’s potential in archeology
Dr. Wearne said that the findings “were the biggest step forward since the development of the original, conventional dating system” in the 1940s.
“It then requires that we think about the social and historical context in which the roles were produced in new ways.”
Andrea Jalandoni, an archaeologist at the University of Griffith who was not involved in the research, said that the addition of other techniques strengthened the reliability of the AI.
“They spelled it with radio cabbage and then evaluated it with expert Palaeographers,” said Dr. Jalandoni.
“I think that is the right way to go with machine learning so that we can trust it.“
But, she said, the AI model was trained on a small sample size, which could make its reliability more difficult.
Professor Popović plans to apply the Enoch model to more Dead Sea Rolls, as well as other old Aramese texts such as the Elephantine Papyri.
“The techniques and methods that we have developed apply to other handwritten [collections of text]”He said.
Dr. Jalandoni, who is studying rock art in Australia and Southeast Asia, said the study gave her ideas for her own research.
“I looked into this and thought,” Wow, I wonder if I can do this with rock art, “said Dr. Jalandoni.
“We have some dates for rock art, but not much.”
Australian Rock Art contains very little carbon, which makes carbon dating a fruitless task, so that archaeologists must rely on other dating methods.
“If we could … a machine learning model make that dates can predict that are in a row with more methods, I think this is the way to go,” said Dr. Jalandoni.
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