Tracking targets on the International Space Station using a laser scanner
Bibliographic record
Abstract
The Neptec Design Group has developed the Laser Camera System (LCS), a new 3D laser scanner for space applications, based on an autosynchronized principle from the National Research Council of Canada (NRC). The LCS operates both in imaging and target centroid acquisition modes. In imaging mode, the LCS raster scans objects and can produce 2D and 3D maps of their surface features. In centroid acquisition mode, the LCS determines the position of discrete target points on an object. The LCS was tested in August 2001 during mission STS-105 of the space shuttle Discovery to the International Space Stations. From a fixed location in the shuttle payload bay, the LCS 1500 nm eye-safe infrared laser was pre-programmed to draw Lissajous patterns on Inconel (black dots on a white background) and retro-reflective disc targets affixed on the Multi-Purpose Logistics Module (MPLM). The LCS acquired centroid data for two and a half hours during the MPLM demating operation to demonstrate its ability to track both types of targets when they are stationary and moving.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".