The Next Generation BLAST Experiment
Bibliographic record
Abstract
The Balloon-borne Large Aperture Submillimeter Telescope for Polarimetry (BLASTPol) was a suborbital experiment designed to map magnetic fields in order to study their role in star formation processes. BLASTPol made detailed polarization maps of a number of molecular clouds during its successful flights from Antarctica in 2010 and 2012. We present the next-generation BLASTPol instrument (BLAST-TNG) that will build off the success of the previous experiment and continue its role as a unique instrument and a test bed for new technologies. With a 16-fold increase in mapping speed, BLAST-TNG will make larger and deeper maps. Major improvements include a 2.5-m carbon fiber mirror that is 40% wider than the BLASTPol mirror and ~3000 polarization sensitive detectors. BLAST-TNG will observe in three bands at 250, 350, and 500 μm. The telescope will serve as a pathfinder project for microwave kinetic inductance detector (MKID) technology, as applied to feedhorn-coupled submillimeter detector arrays. The liquid helium cooled cryostat will have a 28-day hold time and will utilize a closed-cycle 3 He refrigerator to cool the detector arrays to 270 mK. This will enable a detailed mapping of more targets with higher polarization resolution than any other submillimeter experiment to date. BLAST-TNG will also be the first balloon-borne telescope to offer shared risk observing time to the community. This paper outlines the motivation for the project and the instrumental design.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 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".