New results on robust adaptive beamspace preprocessing
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we develop an algorithm for data-adaptive beamspace preprocessing with robustness against out-of-sector sources. Our algorithm yields an orthogonal beamspace matrix and, hence, it preserves the white noise property at the output of the beamspace preprocessor. The beamspace matrix is designed as a matrix filter that maintains an almost distortionless response towards sources within the beamspace sector while maximally rejects all out-of-sector sources. The columns of the beamspace matrix are designed sequentially, one column at a time. This sequential implementation is curried out by imposing orthogonality constraints between beamspace matrix columns. The proposed algorithm is computationally less expensive as compared to the existing data-adaptive beamspace design techniques. Simulation results are provided to validate the robustness of the developed algorithm, and show its effectiveness.
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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 it