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Record W7052536251

Revisiting Pniel 6: the 2017-2019 excavations

2021· article· en· W7052536251 on OpenAlexfundno aff

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
FundersUniversity of TorontoPASTEuropean CommissionQuaternary Research Association
KeywordsColluviumExcavationAssemblage (archaeology)Lithic technologyPleistoceneAlluviumKnappingQuaternarySedimentary rockFaunal assemblage
DOInot available

Abstract

fetched live from OpenAlex

Lithic artefacts from the terraces along the lower Vaal River have been identified since the early 20th century. Pniel 6, in the Northern Cape Province of South Africa, is one such archaeological site known to have revealed both lithics and faunal remains in previous excavations. We re-investigated Pniel 6 with high-resolution modern fieldwork techniques. Our objectives are to reassess the lithic assemblages at the site and to give a precise stratigraphic description of the sedimentary deposits, enabling us to assess the integrity of the archaeological assemblage. We present a report from three seasons (2017-2019) of archaeological fieldwork at Pniel 6 in four new excavation areas. Our results show technological affinities to other transitional Early/Middle Pleistocene sites in the region, but Pniel 6 stands out among them as a lithic assemblage predominantly made from hornfels. Blades and points from prepared cores are frequent, while large cutting tools are absent. The most coherent assemblage, from Area 3, was likely formed through localised alluvial deposition with subsequent colluvial aggregation. The site expands our understanding of the ESA-MSA transition in the interior of southern Africa. It highlights how hominins applied common methods of stone tool production using distinctly different raw materials with varying properties, even within relatively small regional distances.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.264
Teacher spread0.231 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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