Temporal variability in shell mound formation at Albatross Bay, northern Australia
Bibliographic record
Abstract
We report the results of 212 radiocarbon determinations from the archaeological excavation of 70 shell mound deposits in the Wathayn region of Albatross Bay, Australia. This is an intensive study of a closely co-located group of mounds within a geographically restricted area in a wider region where many more shell mounds have been reported. Valves from the bivalve Tegillarca granosa (Linnaeus, 1758) were dated. The dates obtained are used to calculate rates of accumulation for the shell mound deposits. These demonstrate highly variable rates of accumulation both within and between mounds. We assess these results in relation to likely mechanisms of shell deposition and show that rates of deposition are affected by time-dependent processes both during the accumulation of shell deposits and during their subsequent deformation. This complicates the interpretation of the rates at which shell mound deposits appear to have accumulated. At Wathayn, there is little temporal or spatial consistency in the rates at which mounds accumulated. Comparisons between the Wathayn results and those obtained from shell deposits elsewhere, both in the wider Albatross Bay region and worldwide, suggest the need for caution when deriving behavioural inferences from shell mound deposition rates, and the need for more comprehensive sampling of individual mounds and groups of mounds.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".