IAC-04-IAF-B.3.08 512x3 PIXEL UNCOOLED FPA FOR THERMAL INFRARED PUSHBROOM IMAGING
Bibliographic record
Abstract
There are an increasing number of planned earth and planetary observation missions incorporating thermal infrared imaging instruments. The integration of uncooled microbolometer technology into these instruments provides size, mass, and power consumption advantages that are beneficial for small satellite missions and crucial to micro and nano-satellite missions. INO and CSA have developed a unique and versatile Canadian microbolometer technology for satellite missions. This technology has recently been applied to the development of an uncooled focal plane array designed to meet the specific needs of satellite-based thermal infrared imaging. The array consists of three parallel rows of 512 pixels on a 39 µm pitch. Each pixel includes active and reference detectors for on-chip pixel offset correction and increased immunity to die temperature drift. The readout electronics integrates each pixel in parallel, cancels its own offset and low frequency noise and provides 14-bit digital output. A compact circuit card assembly for operating and collecting data with the 512x3 pixel FPA has been designed and fabricated. It fits in an envelope 75mm x 75mm x 50mm and has a power consumption of 3.75 W.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.012 |
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".