**TITLE** ASP Conference Series, Vol. **VOLUME**, **PUBLICATION YEAR** **EDITORS** HI Survey Science with the Canadian Large Adaptive Reflector
Bibliographic record
Abstract
The Canadian Large Adaptive Reflector (CLAR) is a proposed prototype of a new concept for large, filled-aperture radio telescopes. The prototype would have a 300-metre aperture, working up to frequencies of at least 1.4 GHz, and would be equipped with a multi-beam phased array providing a field-of-view of 0.8 ◦ at that frequency. The largest fully-steerable radio telescope in the world, and endowed with a large field-of-view, the CLAR will be uniquely suited for deep spectral imaging over large areas of the sky. Conducted over a period of three to four years, a CLAR Northern-Sky Survey would allow us to simultaneously: survey at arcminute scales the distribution and kinematics of the faint HI in the halo of the Milky Way and High Velocity Clouds; chart the large scale distribution of galaxies in HI out to redshift close to 1; reveal the structure and dynamics of the cosmic web responsible for wide-spread Lyman α absorption systems; image the signal of the reionization of the Universe over a large area with resolution of 10’s of arcminutes. 1.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.162 | 0.135 |
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".