Demo abstract: R.A.V.E.N. — Remote autonomous vehicle explorer network
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
Unmanned aerial vehicles (UAVs) have recently become a viable platform for surveillance and exploration tasks. Several commercial quadrotor aircraft have been successfully used as surveillance equipment with groups such as United States and Canadian police forces, and additional applications for this technology could include exploration of ra-dioactive/hazmat environments, naval search and rescue, or surveying a building on fire, to name a few. Despite the agility and speed of the quadrotor platform, current systems lack the redundancy and collaboration of a multi-unit team; current implementations of quadrotor UAV flocks require expensive equipment, limiting the system to operation within range of external sensors. We propose a system for intelligently controlling multiple quadrotor UAVs using a combination of on-board vision tracking and wireless communication of attitude measurements. The proposed system uses a lead, human-controlled quadrotor and one or more quadro-tors that track and follow the lead unit autonomously. The forthcoming system aims to improve the execution time required to complete missions and increase both breadth of search and platform effectiveness.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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