Dynamic Modelling of the Standard Neonatal Patient Transport System using a Newton-Euler Based Formulation in the Roll Plane
Bibliographic record
Abstract
Transport of neonatal patients between critical care units can expose patients to whole-body vibrations which may pose a risk to the vulnerable patients' health.The concern for patient safety has motivated a study on characterizing and mitigating vibrations transmitted by the Neonatal Patient Transport System (NPTS) that is used in ground and air ambulances in Ontario.To supplement invehicle testing, a simulation is being developed to replicate the motion of the NPTS.The first stage of developing this model involves simulating a planar representation of the NPTS in order to identify unknown system parameters.This paper outlines the derivation of equations of motion of the NPTS in the roll plane by applying the Newton-Euler method.The acceleration power spectral density (PSD) of the simulated motion is compared against recorded road test data to aid in tuning the system parameters.Simulated results show similar frequency responses for the vertical motion of the system.However, the roll direction deviates from the measured response.Further optimization is required to calibrate and validate this model to ensure it represents the angular motion of the system and reproduces behaviour exhibited in various transport conditions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".