Preliminary Performance Assessment of Space-based Observations of Hot-spot Events using Microbolometers
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
Space-based observations of hot-spot events have numerous direct benefits to life on Earth. Such observations would enhance the health and safety of human beings and would protect quality of the natural environment. Hot-spot data can be used for fire detection and fire monitoring, volcanic monitoring, land cover change monitoring as well as studies related to biomass burning, carbon emissions and climate change. This paper discusses a technology development study undertaken by COM DEV Ltd., under a contract by the Canadian Space Agency (CSA), related to the space-based observation of hot-spot events using an imager employing CSA/INO's microbolometer technology. The main objective of the study was to demonstrate the concept feasibility of hot-spot observations using microbolometers. This paper presents a conceptual instrument design, instrument design optimizations, trade-off studies and sample performance analysis results. This paper discusses a preliminary performance assessment of space-based observations of hot-spot events using the COM DEV/INO's multi-channel imager. The suitability of microbolometer detector technology for forest fire observations is discussed. Some future plans and the usefulness of the instrument concept and the performance model for future hotspot observation missions are discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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