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
A new highly reliable gait phase detection system, which can be used in gait analysis applications and to control the gait cycle of a neuroprosthesis for walking, is described. The system was designed to detect in real-time the following gait phases: stance, heel-off, swing, and heel-strike. The gait phase detection system employed a gyroscope to measure the angular velocity of the foot and three force sensitive resistors to assess the forces exerted by the foot on the shoe sole during walking. A rule-based detection algorithm, which was running on a portable microprocessor board, processed the sensor signals. In the presented experimental study ten able body subjects and six subjects with impaired gait tested the device in both indoor and outdoor environments (0-25 degrees C). The subjects were asked to walk on flat and irregular surfaces, to step over small obstacles, to walk on inclined surfaces, and to ascend and descend stairs. Despite the significant variation in the individual walking styles the system achieved an overall detection reliability above 99% for both subject groups for the tasks involving walking on flat, irregular, and inclined surfaces. In the case of stair climbing and descending tasks the success rate of the system was above 99% for the able body subjects and above 96 % for the subjects with impaired gait. The experiments also showed that the gait phase detection system, unlike other similar devices, was insensitive to perturbations caused by nonwalking activities such as weight shifting between legs during standing, feet sliding, sitting down, and standing up.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it