ROS2: a multichannel vision for the robotic REM telescope
Bibliographic record
Abstract
During 2013, a new visible camera has been finally installed and tested at the 60cm, robotic REM telescope in the la Silla Observatory. REM is an Italian, fast-reacting telescope initially designed and built for the immediate response to GRB automatic alerts, but since the first light in 2003 its usage has been covering a wider range of astronomical interests. While the IR camera REMIR was reaching the expected limiting magnitudes, the original ROSS visible camera suffered, since the beginning, of a rather poor performance. We set therefore to implement a newer optical camera, leading to the design, tests and integration of ROS2, a dichroic-based four channels imaging camera. The four Sloan-like pass bands are imaged, at the same time, in four quadrants of the CCD, an Andor multilevel Peltier detector. The tests during the science commissioning show an impressive improvement in the limiting magnitudes, reaching two magnitudes fainter than ROSS. Here we show the concept, the tests and the user level product we are now offering at REM.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".