Technological aspects of traumatic spinal cord injury rehabilitation
Bibliographic record
Abstract
Spinal Cord Injury (SCI) is a lesion that occurs on the structure of the spine channel, and its origin can be traumatic or non traumatic. It has incidence in America between 24 to 54 cases per million per year. Because of many degrees of physical, psychological and social impact caused by SCI, several fronts of study are directed at treating, rehabilitating and reinsertion of this public in society. In addition, there are studies to comprehend how brain reorganization occurs after the injury; to avoid the progression of the lesion and to recover lost functionalities. There have been assistive technologies and brain-computer interfaces (BCIs) developed to improve quality of life and allow more independence and mobility to people with SCI. Many countries of Latin America have limited information about the population with SCI, and due to the high economic and social impact of SCI, there is a huge need of investment in development of technologies for treatments, rehabilitation, low cost assistive devices and BCIs, that could be practical in clinics and accessible to the affected population and care-givers.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".