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 paper presents a 2D flexible printed circuit board (FPCB) micromirror and a scanning 3D light detection and ranging (LIDAR) based on it by integrating the 2D FPCB micromirror with a commercially available single point LIDAR. The 2D FPCB micromirror retains the benefits of previously developed 1D FPCB micromirrors, i.e. large aperture and low cost while providing rotation of the mirror plate about two orthogonal axes to be able to scan a laser beam about both vertical and horizontal axes to achieve 2D scanning. One 2D FPCB micromirror is integrated with a single point LIDAR to achieve a 3D scanning LIDAR, which, in comparison to the previously developed 1D FPCB micromirror based 3D LIDAR, achieved more compact structure and easier fabrication/assembly due to no strict requirement on the alignment between two micromirrors while only one 2D micromirror rather than two 1D micromirrors used. Prototypes of the 2D FPCB micromirror and the 3D LIDAR based on it are fabricated and tested. The test results demonstrate that the 2D FPCB micromirror based 3D LIDAR achieved a volume reduction over the previous 1D FPCB micromirror based 3D LIDAR from 1042 cm 3 to 754 cm 3 with a field of view of 40°× 24° at 150 Hz horizontal scanning and 2 Hz vertical scanning.
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