Concept and technology development for the multispectral imager of the Canadian Polar Communications and Weather mission
Bibliographic record
Abstract
The Polar Communications and Weather (PCW) mission is proposed by the Canadian Space Agency (CSA), in partnership with Environment Canada, the Department of National Defence, and several other Canadian government departments. The objectives of the PCW mission are to offer meteorological observations and telecommunication services for the Canadian North. These capabilities are particularly important because of increasing interest in the Arctic and the desire to maintain Canadian sovereignty in this region. The PCW mission has completed its Phase A in 2011. The PCW Meteorological Payload is a Multi-Spectral Imager (MSI) that will provide near-real time weather imagery for the entire circumpolar region with a refresh period of 15 to 30 minutes. Two satellites on a Highly Elliptical Orbit (HEO) will carry the instrument so as to observe the high latitudes 24 hours per day from a point of view that is almost geostationary. The data from the imagers are expected to greatly enhance accuracy of numerical weather prediction models for North America and globally. The mission will also produce useful information on environment and climate in the North. During Phase A, a certain number of critical technologies were identified. The CSA has initiated an effort to develop some of these so that their Technology Readiness Level (TRL) will be suitable for the follow-on phases of the program. An industrial team lead by ABB has been selected to perform technology development activities for the Meteorological Payload. The goal of the project is to enhance the TRL of the telescope, the spectral separation optics, and the infrared multispectral cameras of the PCW Meteorological Payload by fabricating and testing breadboards for these items. We will describe the Meteorological Payload concept and report on the status of the development activities.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".