ActiveSwingAsymmetricWalkingIncreaseTrunkKinematicVariability.jl: Supporting code and data for the paper "Active Arm Swing and Asymmetric Walking Leads to Increased Variability in Trunk Kinematics in Young Adults"
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<strong>ActiveSwingAsymmetricWalkingIncreaseTrunkKinematicVariability.jl</strong> This repository contains the Julia code, Jupyter notebook, and dataset used in the study "Active Arm Swing and Asymmetric Walking Leads to Increased Variability in Trunk Kinematics in Young Adults" by Mezher et al.. <strong>Instructions</strong> To run this analysis on your computer, both Julia and Jupyter Notebook must be available. A version of Julia appropriate for your OS can be downloaded from the Julia website, and Jupyter can be installed from within Julia (in the REPL) with <pre><code>] add IJulia</code></pre> Alternate instructions for installing Jupyter can be found on the IJulia github or the Jupyter homepage (not recommended). From within the main repository directory, start Julia and then start Jupyter in the Julia REPL <pre><code>using IJulia notebook(;dir=pwd())</code></pre> or if using a system Jupyter installation, start Jupyter from your favorite available shell (e.g. Powershell on Windows, bash on any *nix variant, etc.). In Jupyter, open the <code>Analysis.ipynb</code> notebook. Running all cells will reproduce the results and sole figure of the above mentioned paper. <strong>Description of data</strong> The <code>data</code> directory contains the demographics and raw data. Each <code>.mat</code> file contains gait events, including*: <code>LFO</code>/<code>RFO</code> (Left/right foot lift-off) <code>LFC</code>/<code>RFC</code> (Left/right foot contact) Data signals found in each <code>.mat</code> file are as follows: <code>FP1</code>/<code>FP2</code> (left and right force plates, respectively) <code>LFootPos</code>/<code>RFootPos</code> (Left/right foot COM position) <code>LFootLinVel</code>/<code>RFootLinVel</code> (Left/right foot linear velocity) <code>LFootVelwrtPelvis</code>/<code>RFootVelwrtPelvis</code> (Left/right foot linear velocity, relative to the pelvis) <code>LFootAngle</code>/<code>RFootAngle</code> (Left/right foot angle, relative to the lab reference frame) <code>LFootAngVel</code>/<code>RFootAngVel</code> (Left/right foot angular velocity, relative to the lab reference frame) <code>LShoulder</code>/<code>RShoulder</code> (Left/right shoulder angle, extracted in the order SAGITTAL-FRONTAL-CORONAL) <code>LHip</code>/<code>RHip</code> (Left/right hip angle, extracted in the order SAGITTAL-FRONTAL-CORONAL) <code>TrunkPos</code> (Trunk position) <code>TrunkAngle</code> (Trunk angle, relative to the lab reference frame) <code>TrunkLinVel</code>/<code>TrunkAngVel</code> (Trunk linear/angular velocity, relative to the lab reference frame) <code>COG</code> (Whole-body COM/COG) <code>COG_Velocity</code> (Whole-body COM/COG linear velocity) <code>ModelAngMmntm</code> (Whole-body angular momentum--WBAM) Units for all data are standard Visual3D units. Output variables in the <code>results.csv</code> file: <code>left_steplength</code>/<code>right_steplength</code> (Left/right average step length) <code>SD_left_steplength</code>/<code>SD_right_steplength</code> (Left/right step length standard deviation) <code>left_steptime</code>/<code>right_steptime</code> (Left/right average step time) <code>SD_left_steptime</code>/<code>SD_right_steptime</code> (Left/right step time standard deviation) <code>stepwidth</code>/<code>SD_stepwidth</code> (Average step width and step width standard deviation) <code>lvmean</code>/<code>avmean</code> (Mean of the average linear and angular velocity for each stride) <code>lvstd</code>/<code>avstd</code> (Mean of the standard deviation of linear and angular velocity for each stride) <code>lvmax</code>/<code>avmax</code> (Mean of the maximum (peak) linear and angular velocity for each stride) <code>WBAM_mean</code>/<code>WBAM_std</code> (Mean of the average and standard deviation of WBAM for each stride) *Variables named <code>TRST</code>, <code>TREN</code>, <code>SLST</code>, <code>SLEN</code> are present, but empty, and should be ignored.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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 it