Investigations using ground penetrating radar (GPR) at a maya plaza complex in belize, Central America
Bibliographic record
Abstract
The University of Calgary has conducted a number of ground-penetrating radar (GPR) surveys at the Maya archaeological site of Ma'ax Na since 2001. In an attempt to assist archaeologists working at the site, our research has focussed on improving the quality of the GPR images, highlighting any anomalous features and discerning near-surface stratigraphy. Several 2-D lines and two 3-D grid surveys were acquired across a Maya plaza complex using Sensors and Software's Noggin@ and Smart Cart@ System with antennae frequency of 250 MHz. The hyperbolic fitting of curves to point diffractors indicates significant differences in velocities between field seasons. We attribute this to varying climatic conditions (dry in 2003, wet in 2002). Measured velocities in 2002 ranged from .072 - .lo6 mlns, while velocities ranging from 0.122 - 0.140 mlns were found in 2003. Standard seismic processing algorithms and programs were adapted to the GPR data. The application of a processing flow resullted in improved resolution and continuity of events on the GPR. records. A GPR synthetic radargram was generated based on archaeological information from an excavated pit. Interpretation of the GPR images across the plaza has highlighted a number of interesting features.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".