DEVELOPMENT OF THE BRICAN TD100 SMALL UAS AND PAYLOAD TRIALS
Bibliographic record
Abstract
Abstract. The Brican TD100 is a high performance, small UAS designed and made in Brampton Ontario Canada. The concept was defined in late 2009 and it is designed for a maximum weight of 25 kg which is now the accepted cut-off defining small civil UASs. A very clean tractor propeller layout is used with a lightweight composite structure and a high aspect ratio wing to obtain good range and endurance. The design features and performance of the initial electrically powered version are discussed and progress with developing a multifuel engine version is described. The system includes features enabling operation beyond line of sight (BLOS) and the proving missions are described. The vehicle has been used for aerial photography and low cost mapping using a professional grade Nikon DSLR camera. For forest fire research a FLIR A65 IR camera was used, while for georeferenced mapping a new Applanix AP20 system was calibrated with the Nikon camera. The sorties to be described include forest fire research, wildlife photography of bowhead whales in the Arctic and surveys of endangered caribou in a remote area of Labrador, with all these applications including the DSLR camera.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".