Evidence for Spatially Correlated Gaia Parallax Errors in the Kepler Field
Bibliographic record
Abstract
Abstract We present evidence for a spatially dependent systematic error in the first data release of Gaia parallaxes based on comparisons to asteroseismic parallaxes in the Kepler field and provide a parameterized model of the angular dependence of these systematics. We report an error of mas on scales of 0.°3, which decreases for larger scales to become mas at 8°. This is consistent with the ∼2% zero-point offset for the whole sample discussed by Huber et al. and is compatible with the effect predicted by the Gaia team. Our results are robust to dust prescriptions and choices in temperature scales used to calculate asteroseismic parallaxes. We also do not find evidence for significant differences in the signal when using red clump versus red giant stars. Our approach allows us to quantify and map the correlations in an astrophysically interesting field, resulting in a parameterized model of the spatial systematics that can be used to construct a covariance matrix for any work that relies on TGAS parallaxes.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".