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
1. Materials for dynamic holographic 3D display 2. Photopolymerizable nanocomposite materials for holographic applications 3. Photopolymers for the recording of holographic waveguides 4. Shrinkage in holographic recording materials: photopolymers 5. Advances in holographic photorefractive materials and devices 6. Industrial-scale recording material and mass production of vHOEs 7. Non-imaging holographic optics for solar energy conversion 8. Data security and holographic data storage 9. Multimodal 3D data acquisition using digital holography 10. EUV and SXR holography and tomography with compact short wavelength sources 11. Holographic wavefront sensors 12. Holographic microscopy goes incoherent 13. Digital polarized holography for life science applications 14. Using PA-LCoS microdisplays for holographic data storage 15. Playing the piano with the brain: holographic imaging and manipulation of neural activity 16. Holography in astronomical spectrographs 17. Digital holography based on the spatial coherence function 18. Autofocus in holography 19. Interference lithography for nanostructures fabrication 20. Applications of deep learning in digital holography 21. Digital focusing in laser speckle contrast imaging 22. Ultrafast digital holography and spatio-temporal metrology 23. From a conventional digital holography to wide-sense digital holography 24. Building functional 3D waveguide microstructures with nonlinear waves of light References
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 | 0.000 |
| 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