Plant wax biomarkers in human evolutionary studies
Bibliographic record
Abstract
Plant wax biomarkers are an innovative proxy for reconstructing vegetation composition and structure, rainfall intensity, temperature, and other climatic and environmental dynamics. Traditionally used in earth sciences and climate studies from "off-site" ocean and lake records, biomarker research is now incorporated in archeology and paleoanthropology to answer questions relating to past human-environment interactions and human evolution. Biomarker research is generating new and exciting information on the ecological context in which Homo and its closest relatives evolved, adapted, and invented stone tool technologies. In this review, we examine plant wax biomarkers and their use in reconstructing past plant landscapes and hydroclimates. We summarize the applications of plant wax molecular proxies in archeological research, assess challenges relating to taphonomy, consider the role of modern plant ecosystems in interpreting ancient habitats, and examine case studies conducted at key paleoanthropological locations in eastern and southern Africa and Europe.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".