SATzilla2007: a New & Improved Algorithm Portfolio for SAT
Bibliographic record
Abstract
This paper describes the non-contact optical detection of debris material that adheres to the substrates of color filters (CFs) and thin-film transistors (TFTs) by area charge-coupled devices (CCDs) and laser sensors. One of the optical detections is a side-view illumination by an area CCD that emits a coherency light to detect debris on the CF. In contrast to the height of the debris material, the image is acquired by transforming the geometric shape from a square to a circle. As a result, the side-view illumination from the area CCD identified the height of the debris adhered to the black matrix (BM) as well as the red, green, and blue of a CF with 95, 97, 98, and 99% accuracy compared to the golden sample. The uncertainty analysis was at 5% for the BM, 3% for the red, 2% for the green, and 1% for the blue. The other optical detection, a laser optical interception with a horizontal alignment, inspected the material foreign to the TFT. At the same time, laser sensors intercepted the debris on the TFT at a voltage of 3.5 V, which the five sets of laser optics make scanning the sample. Consequently, the scanning rate reached over 98% accuracy, and the uncertainty analysis was within 5%. Thus, both non-contact optical methods can detect debris at a 50 μm height or lower. The experiment presents a successful design for the efficient prevention of a valuable component malfunction.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".