Bibliographic record
Abstract
Abstract A brain lesion is an area of damage, injury, or abnormal change to a part of the brain. Brain lesions may be caused by head injury, disease, surgery, or congenital disorders, and they are classified by the cause, extent, and locus of injury. Lesions cause many behavioral symptoms. Symptom severity generally corresponds to the region and extent of damaged brain. Thus, behavior is often a reliable indicator of the type and extent of a lesion. Observations of patients suffering brain lesions were first recorded in detail in the 18th century, and lesion studies continue to shape modern neuroscience and to give insight into the functions of brain regions. Recovery, defined as any return of lost behavioral or cognitive function, depends on the age, sex, genetics, and lifestyle of patients, and recovery may be predicted by the cause of injury. Most recovery occurs within the first 6 to 9 months after injury and likely involves a combination of compensatory behaviors and physiological changes in the brain. Children often recover some function after brain lesions better than adults, though both children and adults experience residual deficits. Brain lesion survival rates are improved by better diagnostic tools and treatments. Therapeutic interventions and treatments for brain lesions include surgery, pharmaceuticals, transplants, and temperature regulation, each with varying degrees of success. Research in treating brain lesions is progressing, but in principle a cure will only be complete when brain lesions are replaced with healthy tissue.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.184 | 0.096 |
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".