The Use of Multiple Resolution Cross-Correlations to Align Simultaneously Collected Whole-Body Vibration Data
Bibliographic record
Abstract
A multiple resolution cross-correlation (MRXcorr) procedure was created to align 6-degree-of-freedom (DOF) whole-body vibration (WBV) data time histories collected at the operator/set interface (OSI) and chassis of mobile forestry machinery. Three validation tests were conducted to substantiate the use of the MRXcorr. The results of these validation tests indicate that the MRXcorr can accurately determine the phase shift between two identical 6-DOF data time histories, as well as the phase shift between the 6-DOF chassis and simulated 6-DOF OSI data time histories for forestry skidders. The MRXcorr was also found to align actual field 6-DOF WBV data sets collected on the OSI and chassis of three forestry skidders better than a cross-correlation utilizing the entire length of the data time histories with r 2 -values from regression analyses between the two time histories being greater when those time histories were aligned with the MRXcorr 83.6% of the time.
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How this classification was reachedexpand
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".