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
Functional brain imaging techniques appear ideally suited to explore the pathophysiology of freezing of gait (FOG). In the last two decades, techniques based on magnetic resonance or nuclear medicine imaging have found a number of structural changes and functional disconnections between subcortical and cortical regions of the locomotor network in patients with FOG. FOG seems to be related in part to disruptions in the "executive-attention" network along with regional tissue loss including the premotor area, inferior frontal gyrus, precentral gyrus, the parietal and occipital areas involved in visuospatial functions of the right hemisphere. Several subcortical structures have been also involved in the etiology of FOG, principally the caudate nucleus and the locomotor centers in the brainstem. Maladaptive neural compensation may present transiently in the presence of acute conflicting motor, cognitive or emotional stimulus processing, thus causing acute network overload and resulting in episodic impairment of stepping.In this review we will summarize the state of the art of neuroimaging research for FOG. We will also discuss the limitations of current approaches and delineate the next steps of neuroimaging research to unravel the pathophysiology of this mysterious motor phenomenon.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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