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
Abstract This article reviews the performance of optical filters for the 0.005 to 1000 µm spectral region. The filters described operate in transmitted or reflected light and are intended for use in free‐space optics. The theory of two or more filters placed in series or in parallel is presented. The effect of surface reflections on the performance of the filters is discussed. Optical filters can be based on many different physical principles. Brief explanations are given of the modes of operation of filters based on absorption, reflection, interference in thin films, holography, scattering, diffraction, and interference of polarized light. The principal advantages and disadvantages of filters based on these phenomena are discussed. Filters can also be classified according to the functions that they are intended to perform. In this article the following generic filter types are considered: antireflection coatings, neutral attenuators, narrow band, medium‐band and wideband reflectors, short‐ and long‐wavelength cutoff filters, narrowband transmission filters, rejection filters, neutral‐ and color‐selective beam splitters and correction or gain flattening filters. For each of the above filter types, spectral transmittance or reflectance curves are presented that correspond to representative filters based on a number of the above‐mentioned physical principles. Information is provided on how to specify the performance of the various filter types.
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) | 0.001 | 0.001 |
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