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 advantages of reconfigurable robots have been discussed in the specialized literature. Conventionally, reconfig-urability was a direct result of using modular joints. In this paper we discuss the configuration control and recalibration of a different class of reconfigurable robots, one which is equipped with lockable cylindrical joints with no actuators or sensors. Such a robot can be as versatile and agile as a hyper-redundant manipulator, but with a simpler, more compact, lighter design. A passive joint becomes controllable when the robot forms a closed kinematic chain and the joint lock is released. After reconfiguration, the values of the passive joints are computed from the value of the active joints using inverse kinematics of the closed chain. That problem is solved using a globally uniformly asymptotically stable scheme based on Closed-Loop Inverse Kinematics (CLIK). An asymptotically stable reconfiguration controller is also devised that takes the robot from one configuration to another by directly regulating the values of the passive joints. The controller has a rather simple structure, which only relies on the robot gravity and kinematics models. Conditions for the observability and the controllability of the passive joints are also derived in detail, and some numerical results are reported.
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