Reply: Contributions of visual and motor signals in cervical dystonia
Bibliographic record
Abstract
Sir, We appreciate the thoughtful comments from Amlang and colleagues regarding our recent viewpoint (Shaikh et al. , 2016). They raise the important point that the neural integrator responsible for controlling head position relies on visual feedback in addition to feedback from the cerebellum, proprioceptors, and the basal ganglia. To address these ideas Amlang and colleagues analysed the ‘straight-ahead preference’ in subjects with cervical dystonia and compared it with that of healthy subjects. The ‘straight-ahead preference’ is a classic physiological phenomenon in which the reaction time to a novel image appearing in the peripheral visual field is longer if the eyes and the gaze are straight ahead, aligned with the trunk (e.g. Condition 1 in Fig. 1) than if the eyes are turned to an eccentric location and the target appears straight ahead, in line with head or trunk (e.g. Condition 2 in Fig. 1) (Durand et al. , 2012). This privileged visual processing of the straight-ahead direction in humans is of fundamental functional significance. As multi-tasking creatures, we scan the environment while in motion. As a result, gaze often is not straight ahead, but it is beneficial to be able to refixate promptly to targets that appear directly in front to avoid potential obstacles or accidents. Such behaviour would require the brain to have internal knowledge of the relative alignment of the position of the eye (retina) in the orbit, and the position of the head on the …
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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 | 0.000 | 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 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".