Bibliographic record
Abstract
In this paper, we present a simple design of a fast sliding DFT computer. This computer is a cascade of a comb filter section and a modification of the complex version of the Goertzel algorithm. This modification allows for the computation of the N-point DFT in N iterations. The algorithm has the flexibility of computing any portion of the transform domain with arbitrary resolution. The problem of multiplication by the complex coefficient\exp (j2\pik/N)is resolved using a cascade of rotation operators. The smallest rotation of 2π/N is realized using either a dedicated hardware structure or a software routine. In either method, the approximations\sin(2\pi/N\simeqq/2^{m}and\cos(2\pi/N)\simeq1 - (q/2^{m})^{2}/2lead to a very economical implementation. The representation of the exponent k using generalized canonical signed-digit code leads to a minimum number of required rotation operations. The overall efficiency is comparable to that of the FFT when a sliding type of operation is used.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".