THE DOF DEGENERATION CHARACTERISTICS OF CLOSED LOOP OVER-CONSTRAINED MECHANISMS
Bibliographic record
Abstract
A new teminology, “degenerative degrees of freedom”, to describe mechanisms possessing different degrees of freedom (DOF) while containing the same number of linkages and joints is introduced. A systematic approach is developed for studying this particular type of closed loop mechanism and its degeneration characteristics of DOFs. First, the single closed loop over-constrained mechanism is analyzed and a relationship between the number of over-constraints and the number of joints and DOFs is established. Then, all possible types of independent over-constraints and their combinations are summarized. Further the non-instantaneous condition of the mechanism is analyzed by using an analytical method. The paper delineates three rules that provide the guidelines for the layout of joints, linkages and their assembly. Finally, the degenerative characteristics of all such mechanisms are systematically tabulated along with sketches of some typical ones. To corroborate the literature an example involving two 6R closed loop mechanisms with 1 and 3 DOFs respectively is presented and analyzed, thus validating their degenerative characteristics.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".