The elemental analysis of bog oak samples of archaeological interest by ICP-MS
Bibliographic record
Abstract
The archaeological samples in question are Bog Oak that are over 3000 years old and have been excavated fro Garry Bog, Co. Antrim. These trees along with others have been used to build a tree ring chronology that can aid archaeological dating and also track climate changes. Climate changes can be tracked because the width of a tree ring depends on the growing conditions prevalent that year. It was noted in the chronology that in some years of the 11th century B.C. the growth rings were extremely small, denoting very bad growing conditions. This is attributed to the massive eruption of Mt. Hekla in Iceland. The aim of the project was to determine whether chemical data that track the change in growth rings could be gathered from these samples. The samples were divided up into different sections corresponding to separate time periods. Samples were then processed into liquid form and analysed using ICP-MS. The concentrations of several elements were determined. Initial results indicated that the concentrations of a range of elements were elevated in the years following the eruption. However further work only shows this pattern for copper. The data can be said to be inconclusive but can also be seen as a basis for further work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".