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
A need has long existed for a rapid deployment, terrain following security sensor for use around portable resources, along an avenue of approach, or for the temporary replacement of a failed sensor. Existing solutions such as portable microwave or passive infra-red (PIR) sensors are relatively inexpensive, but cannot work over uneven terrain, around corners, or in foliage. The cost and installation complexity of these sensors increases rapidly as more units are required. The Repels <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">reg</sup> RF sensor provides many of the required features, but uses sensor cables that are overtly mounted above ground. The OmniTrax <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">reg</sup> technology was first introduced at the 2004 Carnahan Conference, applying ultra wide band radar principles to a ranging leaky cable guided radar sensor. In 2007, a program called TFDIDS (terrain following deployable intrusion detection sensor) was initiated in conjunction with the US Air Force, to apply the advancements in this ranging technology to the rapid deployment sensor needs defined by the USAF tactical automated sensor system (TASS). This advancement includes a novel invention employing the processing of dual parallel leaky sensor cables, termed Stereo OmniTrax. This processing dramatically improves the discrimination between human intrusion threats and small nuisance targets or environmental effects. The TFDIDS system provides a complete lightweight sensor kit for the rapid deployment (less than 30 minutes) of a 100 m detection zone, and later, for the sensor's retrieval and reuse. TFDIDS interfaces to standard Government Furnished Equipment (GFE) including USAF powering and communications devices. This paper outlines the key elements of the TFDIDS design, describes its components, and explains how TFDIDS provides reliable detection using a surface sensor cable deployment. Initial performance results are presented, from tests conducted at the Senstar SITE in 2008. The test applications include through-the-woods, on tarmac and on typical open field surfaces.
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