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
The border security project 'America's Shield', part of the US's Secure Border Initiative, will see the deployment of new sensors along the borders with Mexico and Canada and provide integration of existing border sensors into a border surveillance and security centre. The history of border security systems in the USA is outlined. If rapid response to border intrusion is to be implemented, then the intrusion must be rapidly detected, verified and a response team dispatched. One of the biggest challenges is to ensure that the technology performs reliably in the harsh environment along the border. The issues associated with the management of video and sensor signals are considered. The false alarm rate of America's Shield must be close to zero. This is accomplished by multiple sensors and fusing the sensor information to provide an alarm only when the intrusion is real. In non-populated border areas the response is inadequate. Tunnels for mass infiltration across the border have been found. These would escape detection by video systems but could be detected by seismic sensors. The lessons that could be learned from the implementation of intelligent transport systems are considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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