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
Summary Singular spectrum analysis (SSA) is a method utilized for the analysis of time series arising from dynamical systems. The method is used to capture oscillations from a given time series via the analysis of the eigenspectra of the so-called trajectory matrix. The trajectory matrix is composed of multiple data views. The singular value decomposition (SVD) of the trajectory matrix can be used for rank reduction and noise elimination. We apply SSA in the FX domain and present a comparison with classical FX deconvolution. The algorithm arising from SSA analysis is equivalent to Cadzow FX noise attenuation, a method recently proposed by Trickett (2008). It is important to stress, however, that Cadzow filtering (Cadzow, 1988) is a general framework for noise reduction of signals and images. Cadzow filtering is equivalent to SSA when considering sinusoidal waveforms immersed in additive random noise. The intention of this abstract is to provide a simple explanation of the basic assumptions made in SSA and its application to the modeling of plane waves.
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 | 0.001 |
| 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) | 0.002 | 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