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 Short‐wave infrared (SWIR) cameras open up numerous possibilities for machine vision solutions, since they detect invisible product flaws as well as desired characteristics: In contrast to mainstream machine vision cameras with CCD or CMOS sensors, most SWIR cameras have an InGaAs (Indium Gallium Arsenide) sensor and thus detect wavelengths between 900 nm and 1700 nm. These wavelengths are invisible to the human eye and CCD or CMOS cameras. Thus, SWIR cameras detect the invisible, for example, water accumulations inside fruits or defects within silicon products. This document gives examples of SWIR camera applications in several fields such as the semiconductor industry, recycling, metal and glass inspection, and airborne remote sensing. Since some SWIR cameras are mainly designed for use in research facilities, not only the image quality is crucial for industrial applications, but also an industrial rugged design as well as camera features commonly used in machine vision applications.
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