TAIGA-HiSCORE detection of the CATS-Lidar on the ISS as fast moving point source
Bibliographic record
Abstract
We report the first ground-based observation of the CATS-LIDAR onboard the ISS by the TAIGA-HiSCORE gamma-ray facility, and the MASTER-Tunka Robotic telescope. HiSCORE detects unscattered laser light directly from the ISS, at up to km-scale distance from the laser beam spot on ground. The ISS-LIDAR turns out to be a unique calibration tool, in particular to verify the absolute astronomical pointing of HiSCORE. We detected the LIDAR for 11 ISS-passages; among these were observations of forward scattering of the laser beam in dense clouds, which might carry information complementary to the LIDAR technique. We expect other air Cherenkov installations like IACTs to benefit from this light source.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".