An Improved Proper-Motion Catalog Combining USNO-B and the Sloan Digital Sky Survey
Bibliographic record
Abstract
An improved proper-motion catalog is presented, combining the USNO-B and Sloan Digital Sky Survey (SDSS) catalogs in the area of sky covered by SDSS Data Release 1 (DR1; 2099 deg 2 ). USNO-B positions are recalibrated using SDSS galaxies, and proper motions are recomputed including both the USNO-B and SDSS positions. Statistical errors in the USNO-B proper motions are decreased by roughly 20%–30%, systematic errors are greatly reduced, and the proper motions are placed on an absolute reference frame. Requiring a match to an SDSS object removes the large number of false high proper motion objects in USNO-B. The resultant catalog is 90% complete to g < 19.7, with statistical errors in the component proper motions of roughly 3–3.5 mas yr -1 , substantially smaller systematic errors, and a contamination rate of less than 0.5%. A number of studies are currently underway using proper motions from this catalog. The catalog is available via ftp.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.018 | 0.023 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.019 |
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".