Measurements of atmospheric water vapor above Mauna Kea using an infrared radiometer
Bibliographic record
Abstract
Astronomical arrays operating at (sub)millimeter wavelengths are seriously compromised by rapid variations in atmospheric water vapor that distort the phase coherence of incoming celestial signals. The signal received by each antenna of the array suffers a phase delay that varies rapidly with time and from antenna to antenna. Unless corrected, these distortions limit the coherence time of the array and seriously compromise its sensitivity and image quality. Building on the success of a prototype infrared radiometer for millimeter astronomy (IRMA), which operates in the 20μm region to measure the column abundance of atmospheric water vapor, this paper presents results obtained with a second generation IRMA operating at the James Clerk Maxwell telescope (JCMT) between January and July 2001. The results are compared with other measures of water vapor available on the summit of Mauna Kea, including: the JCMT SCUBA bolometer camera, the California Institute of Technology (CSO) opacity monitors, the JCMT 183GHz water vapor radiometer and Hilo-launched radiosonde data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".