Human–environment interactions at Ta'ab Nuk Na, a submerged Maya salt works site in Belize
Bibliographic record
Abstract
Abstract Sea-level rise and settlement are investigated at Ta'ab Nuk Na, an ancient Maya salt works in Belize, by examining samples from wooden posts and marine sediment. The samples included Post 145 of Building B and the Nunavut beam, along with marine sediment columns cut from beside both wooden posts. The sediment columns were sampled at 2 cm intervals. Loss-on ignition confirmed the presence of organic material. Identifying the organic content involved removing nonorganic material from the sediment and sorting the organic material under magnification. This procedure established that most of the organic material was red mangrove (Rhizophora mangle). Red mangroves tolerate salt water, but under conditions of sea-level rise, the plants grow vertically to keep their leaves above water. Sediment, leaves, and detritus trapped in the prop roots form mangrove peat, which serves as a proxy for sea-level rise. AMS dating of fine red mangrove roots determined that the local sea levels rose at Ta'ab Nuk Na throughout the Late Classic period and continued into the Postclassic period. Radiocarbon dates obtained from the wood-post samples yielded Late Classic–period dates. Comparing the radiocarbon dates from the wooden posts and the sediment core samples determined that the site was abandoned before the rising seas flooded the area. Evidently, sea-level rise did not play a role in site abandonment.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".