Radiocarbon and Luminescence Age Determinations on Mounds at Crystal River and Roberts Island, Florida, USA
Bibliographic record
Abstract
Optically stimulated luminescence (OSL) has been employed successfully to determine the ages of palaeosols from earthen mounds in the southeastern USA, providing archaeologists with a means of dating monument construction in the absence of carbonaceous materials and geologists with a setting for understanding factors that can affect the luminescence intensity (i.e., burial dose) of soils. However, OSL dating has not been adequately tested on mounds whose principal component is sand, shell, or a combination of these two, despite the fact that monuments composed of such materials are common to the coasts and interior coastal plains of the region. Radiocarbon dating of bone collagen and soil‐carbon and OSL dating of quartz grains extracted from the fill of mounds at the Crystal River and Roberts Island sites on the west‐central coast of Florida, USA are used to determine the timing and history of mound construction at the sites. Comparison of OSL and radiocarbon ages on materials from the same or closely related contexts provides insight into factors influencing age determinations in mound fill deposits, particularly the type of construction material (sand or shell) and the manner in which these were deposited. The results contribute to the understanding of the temporal context of platform mound construction in southeastern USA.
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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 | 0.001 | 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".