The Large Zenith Telescope Survey: A Deep Survey Using a 6-m Liquid Mirror Telescope
Bibliographic record
Abstract
The Large Zenith Telescope Survey whose construction is almost completed (first light expected in spring 2002) near Vancouver (Canada) is designed to observed a total strip of ~17' x 120 deg in 40 medium-band filters spanning 4000-10000 A. It will gather the spectrophotometric energy distributions of ca. \\~10^6 galaxies to redshifts z~1, with redshift accuracy sigma_z=0.01 at s/n=10, sigma_z=0.04 at s/n=3, ca. 10^5 stars, and a large sample of QSOs, variable stars, and transient objects of the solar system. The survey is optimized for studying of the evolution of both the luminosity function and the clustering of galaxies to a redshift z~1. It will also provide a complete and homogeneous sample of stars at various galactic latitudes useful for studying galactic structure, and it will be a good instrument for the monitoring of variable objects.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".