GIS-Based and Statistical Approaches in Archaeological Predictive Modelling (NE Romania)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Archaeological predictive modelling (APM) is an important method for archaeological research and cultural heritage management. This study tests the viability of a new statistical method for APM. Frequency ratio (FR) is widely used in the field of geosciences but has not been applied in APM. This study tests FR in a catchment from the north-eastern part of Romania to predict the possible location(s) of Eneolithic sites. In order to do that, three factors were used: soils, heat load index and slope position classification. Eighty percent of the sites were used to build the model, while the remaining 20% were used to externally test the model’s performance. The final APM was made with the help of GIS software and classified into four susceptibility classes: very high, high, medium and low. The success rate curve and the prediction rate curve reported values of the area under curve (AUC) of 0.72, and 0.75 respectively. The Kvamme’s Gain value for the model has a value of 0.56. Therefore, the final APM is reliable, so FR is a viable technique for APM. The final map can be successfully used in archaeological research, cultural heritage management and protection, preventive archaeology and sustainable development.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it