KINEMATIC ANALYSIS AND PERFORMANCE EVALUATION OF 6R INSTRUMENTED SPATIAL LINKAGES
Bibliographic record
Abstract
Six-degree-of-freedom instrumented spatial linkages are often used to measure anatomical joint motion for clinical studies or research applications in biomechanics. Their appropriate design is a fundamental issue to allow for accurate measurements and ease of application, and this mainly relies on addressing the kinematic analysis of the linkage. The aim of this paper is to integrate and extend past literature in the field by giving a generalized set of guidelines and ready-to-use mathematical relationships to approach the whole kinematic analysis of a general instrumented spatial linkage in a systematic way. The direct kinematics is formulated using common robotics formulation and, with reference to a specific linkage architecture, a geometrical approach is proposed to solve for the inverse kinematics in closed-form. Kinematic error analysis is addressed in a generalized way by using differential transformation theory, and it is then applied to the specific case under study. By the proper definition of a virtual joint, the inverse kinematics is used to estimate the static performance of the linkage over its specific task space.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".