Geophysical Survey, Magnetometry Survey at Clatford Bentazone
Bibliographic record
Abstract
Data collection involved the traversing of the survey area along straight and parallel lines using a Sensys Magneto MXPDA cart-mounted fluxgate gradiometer survey system. Cart traverses had a lateral separation of 2.5m with even coverage being achieved by the use of regularly-spaced markers at the ends of traverses and the real-time positional trace plot on the survey computer. Readings were taken at a rate of 100Hz, equivalent to 0.25m intervals along traverses 0.5m apart, providing an appropriate methodology balancing cost and time with resolution. The Magneto MXPDA has a typical depth penetration of up to 1.0m although this increases if strongly magnetic objects have been buried in the site. Under normal operating conditions it can be expected to identify buried features >0.5m in diameter. Features that can be detected include disturbed soil where it is in contrast to the surrounding geology, such as the fill of buried cut features (e.g. ditches and pits); structures or features that have been heated to high temperatures (magnetic thermoremnance); and objects made from ferro-magnetic materials. The strength of the magnetic field is measured in nano Tesla (nT), equivalent to 10-9 Tesla, the SI unit of magnetic flux density. Magnetometry was chosen as a survey method as it offers the most rapid ground coverage and responds to a wide range of ground disturbance caused by past human activity. These properties make it ideal for the fast yet detailed surveying of an area. The detailed magnetometry survey was undertaken using a Sensys Magneto MXPDA cart-mounted system. The two-wheeled lightweight non-magnetic cart is pushed by the operator and carries an array of five vertically-mounted FGM650/3 sensor tubes with a horizontal spacing of 0.5m and a Carlson BRx7 GNSS receiver. Readings are collected by the MXPDA data acquisition unit and combined with the incoming GNSS location data stream on a Carlson RT4 rugged tablet PC mounted at the rear of the cart. This enables readings to be taken of both the background magnetic field and any localised anomalies. The difference between the background baseline and the localised variations are plotted as positive or negative data points the strength and nature of which can be interpreted to indicate the presence of different types of buried features. All sensors are calibrated to cancel out the local magnetic field and react only to anomalies above or below this baseline. On this basis, anomalies with high variation from the baseline such as those caused by burnt features (e.g. kilns and hearths) or ferrous objects will give a high reading. Cut features such as ditches and pits can be detected due to the differing composition of their backfilling material when compared to the surrounding undisturbed subsoil. Commonly this material contains higher proportions of humic material, which is rich in ferrous oxides, and therefore appears as magnetically enhanced readings usually forming linear features or discrete areas when viewed in plan. The Carson BRx7 GNSS antenna with real-time centimetre accuracy was used to geolocate the data readings taken by the Magneto MXPDA within the Ordnance Survey national grid. The use of a real-time corrected unit enables a high level of accuracy to be obtained both in the field while undertaking the survey and in the geophysical data collected. Data gathered in the field was imported into and processed using the TerraSurveyor 64 software package. This allows the survey data to be collated and manipulated to enhance the visibility of the anomalies, particularly those likely to be of archaeological origin The geophysical survey successfully identified several features likely representing archaeological features, namely enclosures within Field 2 and 4 of the survey area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".