The North Field Excavations at Vindolanda: Preliminary Report on the 2009–14 Exploratory Field Seasons
Bibliographic record
Abstract
Since 2009, work has been carried out in the North Field at Vindolanda, a Roman military fort in the frontier zone of Roman Britain. The excavations have been directed by the Vindolanda Trust, in conjunction with a team from the University of Western Ontario. Based on these first seasons, some significant preliminary conclusions about this area of the site can be made, which will be important in moving forward with further excavations and for future interpretations of the early occupation of this region by the Roman army. The North Field appears to have been occupied already in the last quarter of the first century and may prove with further excavation to contain a fort that pre-dates “Period I” at Vindolanda, settled in ad 85. The field also appears to have been an area of significant activity in the second and third centuries. Large stone structures and a fortified ditch enclosed at least part of the space in this period. These buildings were part of the thriving third-century extramural settlement explored extensively elsewhere at Vindolanda over the past decades. The findings from these five seasons (2009–2010 and 2012–2014) have led to further excavation campaigns in the North Field, which will continue for several more field seasons. This article disseminates the results of the exploratory trenches as the research moves forward with further excavation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".