Hunter-Gatherers Harvested and Heated Microbial Biogenic Iron Oxides to Produce Rock Art Pigment
Bibliographic record
Abstract
Red mineral pigment use is recognized as a fundamental component of a series of traits associated with human evolutionary development, social interaction, and behavioral complexity. Iron-enriched mineral deposits have been collected and prepared as pigment for use in rock art, personal adornment, and mortuary practices for millennia, yet little is known about early developments in mineral processing techniques in North America. Microanalysis of rock art pigments from the North American Pacific Northwest reveals a sophisticated use of iron oxide produced by the biomineralizing bacterium Leptothrix ochracea; a keystone species of chemolithotroph recognized in recent advances in the development of thermostable, colorfast biomaterial pigments. Here we show evidence for human engagement with this bacterium, including nanostructural and magnetic properties evident of thermal enhancement, indicating that controlled use of pyrotechnology was a key feature of how biogenic iron oxides were prepared into paint. Our results demonstrate that hunter-gatherers in this area of study prepared pigments by harvesting aquatic microbial iron mats dominated by iron-oxidizing bacteria, which were subsequently heated in large open hearths at a controlled range of 750 °C to 850 °C. This technical gesture was performed to enhance color properties, and increase colorfastness and resistance to degradation. This skilled production of highly thermostable and long-lasting rock art paint represents a specialized technological innovation. Our results contribute to a growing body of knowledge on historical-ecological resource use practices in the Pacific Northwest during the Late Holocene.Figshare link to figures: https://figshare.com/s/9392a0081632c20e9484.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".