TAOS II: THE ROBOTIC OPERATIONS
Bibliographic record
Abstract
In this work, we present the general procedure for the robotic observations of the Transneptunian Automated Occultation Survey (TAOS II). The project aims to detect small TNOs (Transneptunian Objects) by serendipitous stellar occultations. To do so TAOS II will operate three 1.3 m telescopes equipped with CMOS cameras which are able to read about 10,000 stars in multiple subapertures at a 20 Hz cadence. At such rates, it will be possible to identify diffraction features in the lightcurves, helping us to estimate a distance and object size to each occultation event. TAOS II is installed in the Observatorio Astronómico Nacional in San Pedro Mártir, Ensenada, México (OAN-SPM). The site has good observing conditions, typically with around 260 useful nights per year. Here, we describe the different process to be performed in a typical observing night: system start up and shut down, monitoring observing conditions, acquisition of calibration images, field selection, pointing, camera synchronization, determination of aperture sizes and positions, and high speed image acquisition.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.017 |
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".