Geophysical Survey, Magnetometry Survey at Clatford Bentazone
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».