An analysis of optical pick-up in SCUBA data
Bibliographic record
Abstract
The Submillimetre Common User Bolometer Array (SCUBA) at the James Clerk Maxwell Telescope (JCMT) employs a chopping and nodding observation technique to remove variations in the atmospheric signal and improve the long-term stability of the instrument. In order to understand systematic effects in SCUBA data, we have analysed single-nod time streams from across the lifetime of SCUBA, and present an analysis of a ubiquitous optical pick-up signal connected to the pointing of the secondary mirror. This pick-up is usually removed to a high level by subtracting data from two nod positions and is therefore not obviously present in most reduced SCUBA data. However, if the nod cancellation is not perfect this pick-up can swamp astronomical signals. We discuss various methods which have been suggested to account for this type of imperfect cancellation, and also examine the impact of this pick-up on observations with future bolometric cameras at the JCMT.
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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 | 0.000 |
| 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 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".