Optimization of Discrete Spherical Harmonic Transforms and Applications
Bibliographic record
Abstract
11922.13EGM06 4380x4380 4.66800e-38 23996.16 1.51705e-37 12012.51EGM06 2190x4380 2.69818e-39 1047916. 3.81664e-36 8547.84EGM96 720x1440 3.66309e-38 111.16 5.68844e-38 55.60EGM96 720x720 3.66421e-38 105.75 5.68694e-38 52.77EGM96 360x720 5.54169e-39 460.85 1.40232e-36 25.70EGM06 4320x8640 1.36722e-07 4246.42 3.24734e-08 2209.03EGM06 4320x4320 2.26366e-07 4206.77 7.73083e-08 2197.19EGM06 2160x4320 2.96840e-13 72504.36 2.95338e-10 1077.59EGM96 720x1440 5.96960e-20 8.05 6.44926e-20 3.80EGM96 720x720 5.96996e-20 7.72 9.11931e-20 3.64EGM96 360x720 6.72886e-21 12.58 1.56678e-18 1.84RMS(coef.) Time(sec.) RMS(data) Time(sec.)Synthesis/Analysis SynthesisModel Grid
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".