New solutions for autonomous control and navigation
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
The most precise navigation systems are commonly based on at least 3 laser gyros and 3 mechanical accelerometers, based on moving or tensioned elements. Laser gyro's "dead zone" guides to existence of additive subsystems, and mechanical accelerometer accumulate the "error of zero" and does not measure during the free fall of an object. Here is found that dead zone on laser gyro characteristics is a result of the precession of momentum of pulse of ring baghron. The necessity of precise laser gyro tuning in Alert city, Canada, is discussed. The method to minimize the precession and to avoid the dead zone on the output characteristics is proposed. Therewith new solutions for autonomous control and navigation are discussed. Here is proposed the autonomous unit of sensors of irregular movement without moving parts and without ring laser resonators, disposed motionless on the object to be measured, based on unique unified 6 mini modules of the autonomous resonatory devices (ARD's). Another new solution could be computer 3D-mouse without pad and with 3 independent outputs for each axis of irregular movement, or the gear of control, which could be arranged in the marker or pen. ARD theory, the experiments and testing are discussed.
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