Development of a Dual-Mode Remote Sensor Test-Bed: Integration of the Joint Multi-Mission Electro-Optic System (JMMES) and Multi-Mode Magnetometer Detection System (3MDS) Sensors into the NRC Fly-By-Wire Bell 412 Advanced Systems Research Aircraft (ASRA)
Bibliographic record
Abstract
In 2010 the National Research Council of Canada Flight Research Laboratory (NRC-FRL) completed prototype development and flight test qualification of a remote sensor helicopter platform for Defense Research and Development Canada (DRDC). Based on the NRC Fly-By-Wire (FBW) Bell 412 ASRA, the aircraft is capable of concurrent carriage of the Generation III JMMES (MX-15D electro-optic (EO) camera turret and computing payload) and 3MDS (tow-body sensor and computing payload) sensors. Anticipated air-vehicle applications for these remote sensors include manned and unmanned, fixed and rotary-wing military assets. Sensor airworthiness qualification indicated no adverse flight or structural dynamics, stable tow-body flight dynamics, and no adverse aircraft EMI/EMC characteristics. Sensor functional testing revealed normal 3MDS magnetic noise signatures and MX-15D EO operations. Man-machine interface and human factors engineering (pilot switching, egress) issues were highlighted for improvement. The current flight clearance allows an operational envelope for EO operations to the aircraft velocity-never-exceed (VNE) airspeed of 140 knots. 3MDS tow-body operations are cleared to the aircraft 80 knot slung load airspeed limit. Clearance limitations include a three-member crew, day Visual Flight Rules (VFR) cueing, and FBW systems disabled operations. Over water operations as well as laser operations outside of Canada are currently prohibited. Future enhancements following correction of identified issues include flight envelope expansion as well as development of the capability to interface JMMES and 3MDS with the aircraft FBW flight control system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".