Lithic Raw Material Characterisation at Olduvai Gorge, Tanzania
Bibliographic record
Abstract
Olduvai Gorge is located within the Ngorongoro Conservation Area, a UNESCO World Heritage Site in northern Tanzania along the western margin of the East African Rift System. Olduvai’s sedimentary record exhibits a complex sequence of inter-stratified lithic technologies including Oldowan, Acheulean, Middle Stone Age, and Later Stone Age assemblages. While diachronic technological change is perceptible, one aspect that remained largely unchanged through time was the totality of locally available rock types. This study constitutes Olduvai Gorge’s first systematic survey and characterisation of source lithologies using thin section petrography. The primary objectives of this thesis were to establish the range of available lithic raw materials, petrographically characterise these, and determine if there were unique inter-outcrop petrographic signatures to determine if it is feasible to source lithic artifacts at the mineralogical level. Geological samples were collected in primary and secondary positions within the greater Olduvai Gorge region. A total of seventy-four thin sections of sixty-two geological samples from nineteen sources were analysed. By way of comparative analyses, it is shown that four quartzitic outcrops have unique mineral compositions, four meta-granite varieties are unique to individual outcrops, Engelosin phonolite samples are texturally and mineralogically unique, and magmatic samples recovered in secondary position may be sourced to their volcanic centre. The results of this thesis demonstrate it is feasible to differentiate between source material by way of optical mineralogy which implies that sourcing lithic artifacts from Olduvai is possible. Altogether, these revelatory insights will allow future researchers to glean new understandings of hominin raw material transport, as well as ecological and social behaviour within the Olduvai paleobasin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".