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Record W3048161860 · doi:10.1038/s41598-020-69940-w

The first evidence for Late Pleistocene dogs in Italy

2020· article· en· W3048161860 on OpenAlexaff
Francesco Boschin, Federico Bernardini, Elena Pilli, Stefania Vai, Clément Zanolli, Antonio Tagliacozzo, Rosario Fico, Mariaelena Fedi, Julien Corny, Diego Dreossi, Martina Lari, Alessandra Modi, Chiara Vergata, Claudio Tuniz, Adriana Moroni, Paolo Boscato, David Caramelli, Annamaria Ronchitelli

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsGDG Environnement
Fundersnot available
KeywordsDomesticationPleistoceneGeographyContext (archaeology)Mediterranean climateLineage (genetic)Last Glacial MaximumEarly PleistoceneBiologyDiversification (marketing strategy)ZoologyEvolutionary biologyArchaeologyEcologyHoloceneGene

Abstract

fetched live from OpenAlex

The identification of the earliest dogs is challenging because of the absence and/or mosaic pattern of morphological diagnostic features in the initial phases of the domestication process. Furthermore, the natural occurrence of some of these characters in Late Pleistocene wolf populations and the time it took from the onset of traits related to domestication to their prevalence remain indefinite. For these reasons, the spatiotemporal context of the early domestication of dogs is hotly debated. Our combined molecular and morphological analyses of fossil canid remains from the sites of Grotta Paglicci and Grotta Romanelli, in southern Italy, attest of the presence of dogs at least 14,000 calibrated years before present. This unambiguously documents one of the earliest occurrence of domesticates in the Upper Palaeolithic of Europe and in the Mediterranean. The genetic affinity between the Palaeolithic dogs from southern Italy and contemporaneous ones found in Germany also suggest that these animals were an important common adjunct during the Late Glacial, when strong cultural diversification occurred between the Mediterranean world and European areas north of the Alps. Additionally, aDNA analyses indicate that this Upper Palaeolithic dog lineage from Italy may have contributed to the genetic diversity of living dogs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.359
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations36
Published2020
Admission routes1
Has abstractyes

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