Two-Point Maximum Entropy Noise Discrimination in Spectra over a Range of Baseline Offsets and Signal-to-Noise Ratios
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Bibliographic record
Abstract
The two-point maximum entropy method (TPMEM) is a useful method for signal-to-noise ratio enhancement and deconvolution of spectra, but its efficacy is limited under conditions of high background offsets. This means that spectra with high average background levels, regions with high background in spectra with varying background levels, and regions of high signal-to-noise ratios are smoothed less effectively than spectra or spectral regions without these conditions. We report here on the cause of this TPMEM limitation and on appropriate baseline estimation and removal procedures that effectively minimize the effects on regularization. We also present a comparative analysis of TPMEM and Savitzky-Golay filtering to facilitate selection of the best technique under a given range of conditions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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