Overview of the Sapphire payload for space surveillance
Bibliographic record
Abstract
This paper provides an overview of the satellite based Sapphire Payload developed by COM DEV to be used for observing Resident Space Objects (RSOs) from low earth orbit by the Canadian Department of National Defence. The data from this operational mission will be provided to the US Space Surveillance Network as an international contribution to assist with RSO precision positional determination. The payload consists of two modules; an all reflective visible-band telescope housed with a low noise preamplifier/focal plane, and an electronics module that contains primary and redundant electronics. The telescope forms a low distortion image on two CCDs adjacent to each other in the focal plane, creating a primary image and a redundant image that are offset spatially. This combination of high-efficiency low-noise CCDs with well-proven high-throughput optics provides a very sensitive system with low risk and cost. Stray light is well controlled to allow for observations of very faint objects within the vicinity of the bright Earth limb. Thermally induced aberrations are minimized through the use of an all aluminum construction and the strategic use of thermal coatings. The payload will acquire a series of images for each target and perform onboard image pre-processing to minimize the downlink requirements. Internal calibration sources will be used periodically to check for health of the payload and to identify, and possibly correct, any pixels with an aberrant response. This paper also provides a summary of the testing that was performed and the results achieved.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".