Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Overlay errors can be considered in terms of a hierarchy (Fig. 5.1). Most fundamental are those errors which occur when only a single stepper and ideal substrates are used, and where the latter provide high signal-to-noise alignment signals. This basic set of overlay errors is well described by overlay models, which will be discussed in detail shortly. When more than a single stepper is used, an additional set of overlay errors is introduced, referred to as matching errors. Finally, there are process-specific contributions to overlay that can result in non-ideal alignment targets. A full accounting of overlay errors in terms of a hierarchy is useful for assessing and improving overlay. The control of overlay requires the use of models, because these models are employed directly in the software of wafer steppers when aligning wafers, and the model parameters are changed when adjustments are made to wafer steppers. Overlay models conform to the physics of wafer steppers.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it