On the Validation of SPDM Task Verification Facility
Bibliographic record
Abstract
Abstract This paper describes a methodology for validating a ground‐based, hardware‐in‐the‐loop, space‐robot simulation facility. This facility, called “SPDM task verification facility,” is being developed by the Canadian Space Agency for the purpose of verifying the contact dynamics performance of the special purpose dexterous manipulator (SPDM) performing various maintenance tasks on the International Space Station because the real SPDM cannot be physically tested for 3D operations on the ground due to the gravity. The facility uses a high‐fidelity SPDM mathematical model, known as the “truth model” of the space robot, to drive a hydraulic robot to mimic the space robot performing contact operations. In this research different techniques were studied for practically verifying that the complex simulation facility preserves the dynamics of the truth model of the space robot for space‐representative contact robotic tasks. Based upon the study and many years of experience in developing and verifying space robotic systems, a practical validation strategy including detailed test cases was developed along with a set of quantitative criteria for judging the validation test results. © 2004 Wiley Periodicals, Inc.
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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 | 0.018 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".